S network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Np network . . . . . . . . . . . . . . . . . 20 Dclause network . . . . . . . . . . . . . . PPnekwork . . . . . . . . . . . . . . . . . 3 Process model for MQVE* Add i t iona l pictures on fraanes Z 42 ACKNOWLEDGMENTSThis. resear'.l was supported in part by NSF Grant GJ509E. I am indebted 4ia B i l l Henfieman, Jonathan Slocurn. Michael K. Smi-th, Ken Speaker and Bob Amsler for productive discussians and help ih designirig and debugging the programs described here My thanks to Professor Woodrow Bledsoe for making available the IMLAC- display gnd its operating systems. ,NATU~W LANGUAGE ESEARCH FOR CAI Sponsored by THE NATIOW SCIENCE FOUNDATION Grant GJ 509E Privately circulated as:

TECHNICAL REPORT NL-24

Department of Computer Sciences THE UESIVERSITY OF TEXAS AT 'AUSTIN Apr i l 1975 SEMANTICALLY ANALYZING AN ENGLISlI SUBSET FOR THE CLOWNS mCROWORLD I Int~oduction Several examples of semantically based grammars have appeared in the literature since 1970. The most corttplete of these are wknogradls (1972') outline of a systemic grammar for commanding and questioning the robot hand in the MIT blocks world, ~eidorn' s (1972). rewrite rules for anal'yzing and generating ~nglish descr'iptions and transforming them into GPSS programs, and 'the ATN gramdar of questions for the*Lunar Rocks Data Base presented by Woods, Kaplan and Nash-Webber (1972). Most other grammars of significan size, such as that of the NYU String Analysis Project (Grishman and Sager 1973) and Werous gramrs developed for mechanical translation are largely syntactic in orientation and not easily accessible. Riesbeck also presents a semantic grammar m rne form of a sek of LISP programs to cornput conceptual dependencies (1975).

A difficulty with these reports is that th6 systems using the grammars are typically+ quite large programs--loOK+--and the interactions between the grammar and the rest of the system are frequently quite complicated. The reader who wishes to use them as a basis for constructing small natural language understanding system may we l l be at-a loss as how to-begin. He may have the impression that a natural language pro~essing~aystem is a vast undertaking involving great complexity of programming.

He will not be co'mpletely incorrect in these impres.sione, byt in fact p-ramming a grammar and. aemantic system fot a micrdworld model to underetand a small subaet of English is no lonuer a formidable task. khe 6 vocabulary can 'be restricted to one hundred or so words, a minimally sufficient syntactic and semantic syatem can be expremed in a few dozen rules supported by a dozen or so aemantic functions, and the pragmatics of guch microworlds as the STRIPS robot, the blocks world, or the CLOWNS world presented here, can be modelled very stmply, The siqplest microworld models that comunicete in English require an effort somewhere between a two week homewodc exercise and a graduate term project. CLOWNS represents about 6 man-months of effort so far. But is there any real purpose in studying English communication in these trivial microworld situations? If we mbdel language behavior in one microworld we remain eeveral orders of magnitude short of understanding the genera2 use of the langu~ge in text, or in verbal discourse and equally far from the possible g~al of tnstructing computers In English to accomplish a general run of tasks.

I: remain Incurably optimistic. The generalizations about tiny subeets of language and b+avior that emerge from microworld models gradually accumulate in bur human minda into what may eventually prove sufficient understanding fiv the accompliehment of socrally useful tasks. me initiation rltual of programing a mini-intelligence is a r)ecessary pre-requisite to programming one that is more sophiaticafed.

In this paper, CLQWNS, a simple microworld model is presented with an explicit tutorial intent. A brief grammar is described that accounts for much of the embedding logic of English canstructions; a flystem of transformations of Eng1iah.condtituents to property list representations of semantic network structures is followed by their represen,tation in a dynamic process model that can be operated to produce successive states deecribed by the English. The principles used in the system are.a concise representation of my gleanings from recent literature dnd of course from work of my own and my students. 11 Background In this section only a few of hundreds o'f natural language processing papers are suggested as entries to thelliterature. At least a dozen reviews of this liteyature are available; halker's is not only among the most recent and complete (Walker 1973), but it includes a section that cites the reviews.

Since 1970, the langu'age processing literature has been rich in reports of natural langbage systems that can understand subspts of English with respect to various microworlds. In addition to previously mentioned work by Woods, Heidorn and Winoppad, there are less frequently cited but quite interesting theses by Badre (19.72) That learns to do very simple number problems from text, by Scragg (19-75) that answers questions about food preparation processes and by Bruce (1972) that presents a logic and a system for answering questions about temporal reference. Schank Riesbeck, Goldman and Rieger (1975) have publisheda significant series of papers on Semantic parsing., inference and generation for an Endish subset concerning fairly ordinary human action$. Hendrix, SLocum and Thompson (1973) describe* a systexh for under.s-ding and generating English about commercial transactions and Mmple movements. Hendrift (1975) has also developed a set theoretic system of proteos models for representing natural language meanings. TheSp models are descended from robot problem solvidg research by Fikes and Nilsson 8 (1971) and siki6ssy et. al. (19i3). Harris (1972) provides a tour de force that uses problem solving, inference agd learning methode to teach a robot facts about its microworld. Hobbs (1974) presenta an hpproach to natural language semantics that ig shown to apply to several applications, diagramsto-language,, English and Algol-to-Algol, e tc.

Much of the most recent work by Abelson (1975) , Charniak (1972 ) ,' Schank and Abelaon (1975), .Mineky (1975), Winograd (1975), Bobrow and Norman (1975), Collins and Warnock (1975), Rumelhart (1975) has progressed beyond the question of grammar and semantic systems to that of such larger units of semantic organization as Frameg, Stpry grammars, Plane, Schemes, Drems, etc. Although at this writing most of these formulations still fall short of computational realization, it is clear that the research task of the immediate future is one of formulating and programing structures of organizationrthat will successfully model much more complicated microw~rlds than those presently achieved. A forthcoming book edited by Collins and Bobrow will present many of these ideas.

LISP is still the language of most frequent choice for these experiments and thanks to the prevalence of virtual memories and virtual LISP,)the limitation to inrcore implementations has essentially vaniehed. Many of the programs cited used require from 100 to 300K10 cell8 of smrage. l'he system described in subsequent .eections resides in 32K on a CDC syegern, although our moat recent additions have caused ue to use e virtual mbry version of UTLI$P that was developed by -Wry Tyson. 9 111 Pictor-ial Models Ignoring early w~rk largely lost in the archives of corporate memos, Winograd's language processor is essentialky a first reporting of how to map Englpsh sentences into diagrammatic pictures. Apart from potential applications, the pictures are of great valve in providing a universally understood snecond language to demonstrate the system's interpretation of the English input, While we are still struggling in early stages of how to compute from English descriptions or instructions, there is much to be gained from studying the subset of English that is picturable. Translation of English into other more general languages such as predicate calculus, LTSP, Ruseian, Basic English, Chinese, etc. can provm the same feedback as to the system's interpretation and must suffice for the unpicturable set of English. But for teaching purposes, computing pictures from language is an excellent instrument.

We began with the notion that it should be quire easy to construct a microwcizld concerning-a clown, a pedestal, and a pole. The resulting system cauld draw pittures for such sentences as:

A clown holding a pole balance6 on his head in a boat.

A clown on his arm on a pedestal bglances a call clown or his head. Figure 1 shows examples of diagsamg produced in responBe 'to these sentences.

Ue $roereesed fhen to smtcnces concerning movement by adding land, water, o lighthouse, a dock and aboat. We were then able to draw pictures such as Figure 2 to represent the meanings of: A cloh on his head eaile a boat from the duck to the lighthouse. In the context of graphics, two dimensional in their 3implicfty of computation. An ob j~c t is as a LOGO line drawings ate attractive defined graphzcs program that draws it (see Section VI) A scene is a set of ob~ects related in terms of contact points, A scene can be described by a set of pradicstes (BOAT ABOVE WATER) (ATTACH BOAT* WATEqpl) ( ~ C K ABOVE WATER) (DOCK LEFTOF WATER) (BOAT RIGHTOF WK) (ATTACH DOCYky WATE%) (ATTACH BOATXl+kY DOCSy Orientation functions for adjusting starting points and headings of the programs that draw the ob~ects are requlred and these imply some trigonornetrlc functians A LISP package of about 650 llnes has been developed by Gordon Bennett m p~ovide the plcture making capablllty

What 1s rnalnly relevant,to the computation of language meanings 1s that a semantlc structure sufficient to transmlt data to the drawing package is easlly represented as a property list associated ulth an artlficlal pm e for the scene For example, A CLOWN ON A-PEDESTAL" results in the following stbqture (Cl, TOK CLOWN, SUPPORTBY C2, ATTACH(C1 FEET= C2 TOPXY)) (€2, TOK PEDESTAL, SUPPORT C1, ATTACH(C2 TOPXY Cl FEETXI)) (CLOUN, EXPRCWDAO ,) FEET XI , SIZE 3, STARTPT XY, HEADING A) (PEDES~AL. EXPR(LIU.IBDA() ) TOP XY, SIZE 3. STARTPT XY, BEADING A) A larger scene has more objects mare attach relations, and may ~nclude addltlona2 relations such as INSIDE, LEFTOF, RTGHTOF, etc In any case the scene is, s'eaantlc+lly represented as a set of objects connected by 13 relations in a graph (1 e a semantlc network) that can easllj be stored as a property list wlth references to other objects with property lists We take "balance" stand' l r support "hold ' is on" etc. as state describing verbs in contrast to those such as "sail", ' ridef , fly ' "buy etc whlch descrlbe changes of state To model the meaning of state verbs requlres only a single diagram to show the state described Far change of state verbs a serles of plctures 'is required and a process model IS used to construct a sequence of state descrlptlons each of vhlck can produce a diagram IV An Engllsh Subset Grammar ATN as a baslc formalism f ~ describing r a grammar system has been well-described by Woods (19M), lts semantics by Simmons (1973) and a UTLISP version was & Slocum (1972) Whlle generally ignoring theoretical we do use such principles as the fact that sentences structure 01 in a langr~age of fumtlons and arguments such the.€ollowinp grammar and semantlc system our emphasis the highly dariable nature of Fnglish embeddings This bean more interested in the many forms of dependent

We take the Woods computationally This application to Engllsh programed by Matousek lssues In linguistics, are composed of constituents, that there are syntactx rules definlng acceptable sequences of constibuents. and that.underlying the Engllsh statrment there is an idea that can be expressed in Sume other language by transformations on the Engllsh constituents The underlying idea can be expressed in a formal language such as some version of predicate logic, or in a computer data

In presenting ~s on dealing with means that we have 14 clau~e--~re~ositiondl phrase, relative clause, inf lnitive, participial phrase, relative cpnjuetive clause, etc,--than in the ffne detail on noun phrase, noun-noun combinations; and the fine grain of verb sttings We have also for the moment ignored ordinary conjunctions in view of the clear treatment offered by Woods, Wipograd and Grishman; each of whom points out that an and or an "~r" triggers a special subgrammar that attempts to find a structural repetition of a constituent that was just cbmpleted. Bqcause of our interest in embeddings we have chosen to consider relative clauses at the toplevel of the grammar where possible.

The following constituent description defines a very fluid subset of English with great potential for embeddings. CLAUSE NP VP I? G DCLAUSE PP BEUDNJ RELCMUSE PRONCUUSE vMoD VPAST 'VINF VPRESPART -, (NP) + (VP) -+ (DCLAUSE) + CLAUSE 4 ('APT) +. (ADJ*) + N + (DCLAUSE) -+ PRON + (DCMU$E) + VG a + (NE') - (AUX*) + (ADY) + v + (ADV) -t PPI RELCON'JI~RELCLAUSE\~ VMOD + PREP* + NP -, RCONJ + CLAUSE -+ (RELPRON) + PRONCLAUSE -t VO( WP + ,VG .+ (DCLAUSE) +~PA~T/~P(~PR~~PART/vPIvINF/~ '+ SUPPORTED SAILED, . . -+ TO SUPPORT, . , . +.SUPPORTING, SAILING,.. RELPRON -+ WHO, WHICH,, WHAT THAT RGONJ -, BEFORE, AFTER WHILE AUX -+ IS WAS; HAS, HAVE, Hw ADV + ' HDRIZONTALLY. VERTICALLY V SUPPORT $ALAPJCE, SAIL PRON + F@, SHk, ET , THEY ., ART + A, AH, THE ... AD5 -+ LARGE, SMALL, TINT' 1N + 'CLOWN. 'PEDESTAL, BOAT, DOCK,'FEET, TOP, SIDE .., In the a'bove: + means "followed by7, (x) means optional x . x* pedns 1 or more \I means "or", . . . means etc. ,. md x/y means x is the lnitia "element of p. The arrow.+ means "defined by:'.

The form of notation above-is a concise recurgive description fcr the ordering of constituents. It shows nothing abqt the semantics that may be included in the sp t em , and the flow of control far parsing is not at all wbvious. Augmented Transition Netwcwk.graghs foLlowing Woods show the conditions,on elements of the sentence and the f low of control in terms of directed arcs leavlng*nodes in a two-dimensisned diagram of the grammar Even more irnpartantly, an ATN proviaes f ~ the r display of semantic operations that are to be undertaken on each const2tuent. The convention for drawing an ATN is to write conditional statements above the arcs, and operations below. For example : S ;= NP + VS-4- NP fl P,USH NP. PUSH VS PUSH NP,' GTR SUB (PUT(LAST(GETR V3) (PUT (LAST(GETR V). ) "SUBJ(GETR SUBJ) ) "OBJ [GETR OBJ) ) In this net, if the sentence begins with an NP, the PUSH NP will return Ehe structurk of an NP iq the * registei. At that point the registex SUBJect is set to 'that value. When a VString is analyzed. by PUSH VS 'then V is set to the value'VS returned. At this point further structure is bvllr-by PUTting on the verb's property lisk the attribute SUBJ with the value contained $n the register SUBJ. Similarly, when an OBJect NP is parsed, it can be added to the structure of V and,the value of S can be POPped-4.e. returned--as the register V>which will allow access to the property list of rhe verb on which the values of subject and object can be found by consulting those properties as in (GET (LAST(GETR V)) "SUBJ) . The function LAST is used in thi's exhmple to obtain the last element of a list.

Notice this e~ample illustrates.that our general approach to recording vsemantic information is one of putting detailed information such as the arguments or cases of a verb on the property list of that object. Thus the result of parsing "clowns hold, poles" with the above net is:

(HOLD SUBJ CLOWNS, OBJ POJ+ES) In,fact, it is necessary to create new names for each word used in a sentence--to avoid clobbering dictionary information--so the result from actual nets would be: (C1 TOK HOLD, SUBJ* C2, OBJ C3) (C2 TOK CLOWNS, NBR PL, DET INDEFj (C3 TDK POLES NBR PL, DET INDEF) Tke:- relation TOK shows that C1 is, an instantiation of'-the lexiix.11 item HOLD. In this convention for stating property list values, IS the first element is the ATOM and each pair separated by comas an ATTRIBUTE and i-ts VALUE.

The Wdods system also btores it$ pa-st states and provides for backup in the event that no conditional arc succeeds and yet there is still sentence to be scanned., In this event the system recursively consults the state leading to the current node'to see-if there were arcs that wer.e untried that lead to a successful parsing for the sentence string. T-he * register has special sigdficance in that ordinarily it contains the sentence element under the scanner, except wheo a subnet such as NP returns a value, in vhidh case the POP arc sets the value in the * register. The overall flow of control through an ATN is that * is set to the first element of the sentence, then the topmost net, CLAUSE ot S, applies the grammar in topdown fashion. Each the a constituent --a word, a'phrase, a clause--is recognized and control is passed to another notie, the scanner' is advanced and parsing proceeds from the new node. For programing simple grammarg without much embedding and without backup capabilities a~1 ATW may be used a8 a flow chart to design the program. If more complex grammars are requhed, Woods has provided a complete set of language conventions -and gn Interpreter with the capability 18 of storfqg past states and backup. hxicdn t English wpsds; their lord claerres a d f eaturea and other information such ae program definitioos etc. are recorded on a property list structure for eady access by fun&tions used in the ATN. The follow ing examplee illustrate this structure:

(cW (N T) (NBR SING) (EXPR (LAMBRA(). . . .)). . .(FEET XY) (ANIM T)) (BALANCE (u T) (%ENS@ PRES) (EXPR(LAMBDA(ST). . . . )) ) (ON (PREP T) (EWR(LAMBDA(N1 N2). . .) ) (WRO~ (P~N T) (NBR (SING PL)) (PERSON T) (RELPRON T) ) The fuaction (PUT X Y 2)--e.g. (PUT "CLOWN "NBR ''SING)-YI~~ add the pair (Y 2) to the atom X or replace the value of X's attribute Y with the new value Z. The function (GET X P) will then return the value Z. Such ATN functione as CAT ahd GETP simply call GET tdth the first argument set to the value of the word under the sentence scanner.

The l$XPR yalues associ'ated with an Engaish word are aedt ic functions that are explained later. b y modificaticms to this simpjrr? spheme can be aaded to provide for morphorogical variants referring-to root f o m instead> of rhquiring a. definition oi-thef r own, and an attribute; POUOWEDBY, can be used to cbllact multiple ward terms. The basic property list representation of a dictionary can be expanded to include multiple word senees as well, but it always re,tains the character aE a basic LISP syetem for storage and retrieval of data aesaciated with an atom, / / PUSH DCLAUSE SNT F PUSH VPfSENDR SUBJ POP (GETR HD) T HD + * (EVAL ('(GET * IITOK) *I TST CL1 (GETR £ID) POP (GETR m) (NULL Sl?TC). . , Gltammar: This is thk toplkvel net for the grammar. I$ is named clause and transfers control to states C1 and C2 each of which can POP a value in the event that the sentence string has been completed or a clause successfully paased. The barred pointer,* , -indicates a HOP, operation which passes control without advancing the sentence changing the * register.

This net accepts sentences beginning with an NP, a VP or clause. [.ID is the name of a register that generally contains constituent found. The UNHOLD arc emanating from C1 causes a to be processed. HOLD contains Dependent Clauses that are missing soare element that delays their semantic processing. Phx example, "on his nose" in "on hie nose a clown balances" caanot be eema@,~fcally procesped until ll~lovnl' ehovs up as a following NP. The net ie satisfied by a sentence or-by a single noun phrase euch ae 11 a clown in n boat" dr by an imperative, "balance a pedestal". It ddee not ac'cept queetion forms; that would require an additional arc from CLAUSE labelled, PUSH QFOBN SNTC. The ordinary form of an arp is an arc-label such as CATegory, PUSH,, POP, TST followed by its arguL ment, followed by any-condition statement. SNTC is simply the variable that scanher or a dependent the last list, HOLD, 20 contains any remaining sentence string, so the condition SNTC is true except when thelstring has been..exhausted. If SNTC is nil, there is no point in further processing.

The arc PUSH W (SENDR sUBJ)~will send the value of the register SUBJ to the qubnet W.* If VP is SUCC ~ S S ~ the ~ ~ , operation under the qrc (EVAL-((GET * TOK) * )) w i l l caJ1 for a function associated with the verb to translate the subject, ~b jec t and complements of the sentence into the particular semantics of pictorial relations. The verbs SUPPORT, SAIL, and MOVE are defined as semantic functions in seetion V. PreA positions are also defined as semantic functions in that section.

When HD is popped from C1 or C2 it contains the name of an object ondthe property list as described earlier. The resblt of a parse is an atom name whose property list contains labelled references to its arguments which are either symbolic or numeric values, or references to other atoms which have property lists. ~h"is of course is a property list representation of a semantic network.

I' CAT PRON h~ f- (ANTEC * GLST)

1 DET + DEF C I (NP~) POP HD (PUT HOI .I TCT CIY T DET 4 INDEF CAT NI HD (MAKETOK*) PUT HD "DET DET

"MOD MOD * SENDR is usually signified in the nets by ). Thus + SUBJ meansq

(SENDR SUBJ (GETR SUBJ)) X + Y meana (SETR X (APPEND Y (LIST (CETR X)) ) ) This NP net is operated dh the tall, PUSR NP T. It allows for a prono--or a sequence of (arr)(adj*) N. Its operation intludes some basic semantic transformations on the head nbun. If the sentence begins with an-ARTtcle, the determination is set to DEPINITE or INDEFINITE depending on what feature GETF finds associated wdth it. A pronoun implies definite determination, and a noun phrase withouban article implies indefinite exceptdn the case of proper nouns not considered in this net, Adje'ctives are appended to a list named MOD. When the noun head is encountered, MAKETOK creates an atomic name ~i using the LISP function (GENSYM C) and puts on its property list, the pair, TOK WORD. The remaining operations under the CAT N arc add property value pairs to this TOKen of the noun. From NP2 the atc, POP HD (PUTMODS HD), is encountered. PUTMODS is a semantic function that works with adjectives and adverbs iri the following fashioe:

An adjective, e.g. big, has the following lexical structure:

(BIG ADJ T, POS T, TYPE SIZE, VALUE 7) PUTMODS will for each adjective obtain the TYPE and VALUE and put them on the noun's property list. Thus, "a big red clown" results in:

(C1 TOK CLOWN, DET INDEF, NBR SING, SIZE 7, COLOR 1) where COLOR 1 assumes that some mechanism for assigning colors likes numbers as inputs, even as the drawing programs require numerical values for 3IZE.

The result of parsing a noun phrase with thismetwork is to return the semantic structure of an object as a set of property-value pairs associated with the name Ci which is a tbken of the word used. The net is not sophisticated as NP definitions go, much more complete grammars of the NP are offered by Winograd and Woods. The lack of a continuation into a modifying 22 clause such as a PP ordrelaYive clause is deliberate in that we prefer to rbturn control to the structure calling the NP so that its syntacticsemantlr position in the higher sequence can be used by the Dependent Clause net. r 'PUSH NP SNTC

OBJ + 3

PUT Vt 'SUBJ SUBJ 'if "OBJ'OBJ PUSH PP "BY PASV TST AUX=BE V=ED PA$V + T OBJ+ SUBJ SUBJ t NIL SUBJ +- * PUT v !ISUB-J SUBJ PUT Y "OBJ OBJ POP v (PUTI v I'SUBJ SUBJ) t

This VP net first pushes a VG, verb group. VG is not shown in this discussion, but it scans the sentence string for an acceptable sequence of auxilaries, and adverbs domindt'ed by a verb. It makes a token of the verb and puts its tense and auxidiaries on that token as property value pairs. It returns the token name. In exiting node VP1 we seek an NP as a syntactic OBJect and finding one, add the subjgct and object as properties of theverb. If no NP folloys the verb, the next arc tests to debermine whether the verb is a passive form and if so sets the flag PASV, sets object to subject, and subject to nil. If a "by" prepositional phrase follows, it becomes the subject. Additional modifying phrases are picked up by the DCUUSE loop. No actlons are associated with PUSH DCLAUSE arcs 23 because each DCLAUSE calls semanti,~ routines that bind the modifier to the noun or verb it modifies--frequently not the one it ilnmediately follows * The YP net accepts a verb, a verb group, or a verb group followed by an NP and a string of PPs or other modifying clauses. It lacks the case of two NPs to account for direct and indirect objects. h rl PUSH PI' (GAT PREP)

* A HD + POP HD T 4 PUSH RELCONJ (CAT CAT RPRON SUBJ + (ANTEC * GLS? J. SUBJ CAT v "ED "TNG 11 P * = "TO. NEXT = V

The DCLAuSE.net is fairly accounts PPs, relative pronouh clauses, infinitive modifiers, participial c Wses and clauses introduced by relative conjuncti~ns. A PP is w e or more prepositiotrs followed by an NP. A RELCONJ starts with an RCONJ such as "while", "after1' etc. and may be followed by a DCLAUSE or a CLAUSE. A relative, pronoun clause begins with an optional relative pronoun and is followed by a pronoun clause which is either a VP or an NP fohlowed by a VG an6 optional DCLAUSES. For the moment we insist for computational economy that a relative clause he introduced by a relative pronoun; actually the f m of a pronominal clause is sufficiently rwell defined that PUSH PRONCLAUSE can identify it RCONJ) @ PUSH, PRQNCLAUSJ) I TST GETR SUBJ 1 (.EVAL ((GET * T~K) * ) TST 'I ((HOLD *) TST T SUBJ + (VBMATCH * GLST) p , -I. SUBJ HD +intricate in that it for without a relative pronoun -in most cases. When a pronoun is found, here or in an NP, the- function ANTECedent is called to scan the list of prece'ding nouns, to find the best agreement-in person, number, and gender. The function VBMATCA on the exit from node D2 is a function that seeks to find the head that the participial or infinitive phrase is modifying. As in PREPMATCH, the head noun is frequently not the one just preceding the modifying phrase and-the particular verb and its ending are usedl ip choosing its head nauh or verb. GLST is the name of a list of candidates.

In 'the event that the DCLAUSE is a relative pronoun or a participial or infinitive construction, the final step is to call the semntic function associated with the verb and evaluate it for the subject, object and complemeht arguments. DCLAUSE is undefined for adjectival and adverbial clauses that can be used~as modifiers. When defined they can be added as additional arcs. CAT PREP "NEXT U

PUSH NP (GETR PREP*) POP Hb (PREP 4- NIL) PUT "PREP PREP

HEAD + * (PREPMATCH * GLST) This abbreviated PP net is presented to call attenti~n to its method for accepting a ~ t r ing of prepositions and for accomplishing the semantics by calling PREPMATCH. Although Section IV concerns semantics, it is warth noting that the eftect of PREPMATCH is to add information to the semantic structure reptesenting a noun or a verb. For exa~ples: "a clown on a pedestal on his nose I @ (C1 TOK CLOWN*, SUPPORTBY #PEDESTAL, BALPT #NOSE) I1 ... balances on a pedestal on his nose"

(C2 TOK BALANCE, TENSE PRESENT, COMPS (IPE~ESTAL #NOSE) Thus if a verb intervenes beween a voun and prepositional phrases that might ntodify it, the PPs become COMPlements to the verb under the attribute COMPS, and the verb's semantic function has the task of relating it to other elernems of the sehtence. V Semantics of the Subset

Parsing a sentence with the ATN grgmmar just described results in a get of symbols edch of which is further characterized by attribute* and values on a property list. If no semantfc functions were applied--such as those associated with prepositiwns, modifiers and verbs--the result would be a tree such as the following:

(C1 TOK BALANCE, SUBJ (C2 TOK CLOWN, DET DEF),

OBJ (C3 TOK POLE, DET INDEF) , COWS (C4 TOK HANDS, POSSBY C2, PREP (XI))

ie effect a£ the sernaotic functions for this sentence is to produce the f t llowing :

(C2 TOK CLOWN, SUPPORT C3, SIZE 3, ATTACH ((22 C3 )) XY XY (C3 'OK POLE, SUPPORTBY.C2, SIZE 3, ATTACH (C-3 C2 )) xy SY which is minimally sufficient information for the graphics to produce a single icture to represent the state of affairs the .sentence described.

It s perfectly feaslble to compute the syntactic form first and then apply the semantics, but as Winograd, Riesbgck andmothers have found, the early application of semantics can be used to minimize the ambiguities of the syntax. For this reason, as each prepositidnal phrase is parsed a semantic function is called to determine which noun or verb might be its governor or head. Each time a Verb Phrase is completed, a sema~tic function is called to translate COWS, into pictorial relations

Semantics of Prepositiops: its syrltactic arguments, i.e. SUBJ, OBJ, such as SUPPORT, ATTACH points, etc.

After a PP constituent has been identified, a function PREPMATCH is called with a list of the nouns and verbs so far encountered, GLST.! Each preposlition is associated with a function that examines a candidate head from GLST-hnd the naun object to decerpine if candidate can dominate the PF in question. For example "ON1' is defihed a LISP function with two arguments. When called with '"clown'! and "nose", ON returns a structure in which the ATTACH poifit of the clom i's the XY coordinates of his nose. When called with "clown" and1"pedestal" it returns a structure in which the pedestal SUPPORTS the clown. If dallad with "nose" and "pedestal" it returns NIL sihce nose is neither- ah independent picturable object nor a paft of the pedestal.

PREPMATCH does the book-keeping by calling the preposition function with each candidate from the GLST, If*he candidate is a verb tlha~ can be modified by that preposition, PREPMATCH adds the PP to the verb's list: of'C0@S, and the verb gemantic function w i l l interpret it. Tlie function BESIDE offers a simple example definition that shows how dne prepositien can imply another. (BESIDE(LAMBDA(N$ N2) (RIGHTOF N1 N2) )) (RIGHTOF (LAMBDA (N1 N2) (CO'ND ( (AND (GET N1 "PICT) (GET N2 "PIcT) ) the as (PUT N2 "RIGHTOF Nl) (PUT N1 "LEFTOF N2) ) (T NIL) 1 1) Thue. "a beside b" is quite arbitrarily interpret& to mean "b ie ~o the right of a". RIGHTOF requires that its two arguments be picturable objects. "A clown on his nose beside a pedestalr' causes PREPMATCH ((NOSE, CLOWN) PEDESTAL). PREPMATCH first-calls (BESIDE NOSE PEDESTAL) BESIDE calls RIGHTOF which returns I I pecause nose" is not an independent PICTure. Then (essentially*)

Somewhere to mean contact arbitrarily' force a.p.lte~ise meaning--so far suff&ci~rit for our purpose-om the geometrically vague term, "beside". In general the prepositional semantics for a micrpworld model are definable where the number of possible meanings for each preposition are limited by the situation. ~h the CLOWNS wor Id, "with" "on" and "by" have multiple meanings that are selected .in accordance with the conditions described by their semantic functions. In .contrast, "from" so far has a single meaning.

Verb Semantics: The English verb is a remarkably complex conceptual object. It may carry several aeanings dependent on its arguments and on its larger con-text. It communicates information about temporal ordering of its process by auxiliaries and its suffix. It implies one or a sequefitial seriee of events. Its syntactic positi6n and ending can be used to signal

that it is a pre-modifier or a post-modifier for another verb or a noun.

It is part of a clasqification structure and may imply special argument valuee to some more general verb higher in the classification. Far example. * Where these examples use words trhe functions are using C i tokens or

words appropriate. PREPMATCH calls (BESIDE CLOWN -PEDESTAL) and the return is PEDESTAL RIGHTOF CL,OWN. else in the forest, the relation RIGHTOF w i l l be interpreted

between leftsi.de and'rightside of two objects. So we.quite 2 8 "retort" means '.'answer sharply" ~h ich means "comutlicate sharply ii~ response to a communi.cationt'. The verB mdy imply Gpecial arguments in another way; the verb, "sail", implies that "someone caused a vehicle ta move through a fluid by a means involving aerodynamics from 'one place to another" If the sentence omits some of these arguments, the verb semantics implies them. Thus we can sail a boat, a kite, an airplane, a saucer, but hardly a locomotive or a desk. If the arguments are idappropriate we can ascend the classification tree and call the statement a metaphor. In addition, the verb allows its arguments to occupy practically any syntactic position in the clause or sentence and must sort theui out oa the basis of semantic informat ion.

By analogy, a verb is a dramatic skit with a variable set of characters that successively relates the character roles to one another over a period of tjme. A verb has a set of a'rguments, case roles filled by semantic objects; it has an initial state, a set of relations among its characters; a set of intermediate states, one or more sets of relations among its characters; and a final or resulting,,state similarly charafterized. In addition, receht work particularly by Abelson and Schank suggest that in a given culture a verb models a situation that is predictably preceded and followed by rntrre or less typical situations. If a person strikes another person,,the first one was probably angered by the second, dominates the second, etc. while the second, feels pain, map react in anger, etc. So it is reasonable to scppose that our experience is organized in scripts, frames, scenes, dremes, etc. whose component elements include the dynamic skits that verbs signify

In the CLOWNS world a verb selects an associated semantic function to sort its arguments into typical roles in its picturable dr.amatXc skit and relates them in typical ways for display as initial, intermediate and Final conditions. In this rashion, the verb "sail" relqtes an Agent, a Vehicle. a Medium, a Start point., Inmrmediate points, a Goal point and possibly a Means of movemant. #The semantic routine must translate syntactic entities such as Subjec~ Objecr ana Complements into these roies, i.e. bind the variables. It must then relate them'iii iippropriate ways-- AGENT 'IN VEHICLE. VEHICLE AT STARTPOINT, VEHICLE'ON MEDIUM, etc.--for each of its temporal states and call the graphics sysrern to display them.

Support is a. verb that describes a static Single state of af€a.irs in "The world is supported on a turtle 's back". The verbs "balance", '.'support", ''stand'' "huld". are each as-sociated with the semantlc tunct ion SUYPUK'I'~. When a VP constituent using one oi these verbs is completed, SUPPORT1 is called to compute a m,odel of the situation described.

SUPPORT1 binds the THEME and the other two following diagram shows Thl supports TM2 on its arguments are bound. the suqport not. means are taken to till in. the missing arguments by 2 default logic. SUPPORT1 takes as arguments, SL5J, OBJ, and CflMPS where COWS is a list of complements. SUBJ and OBJ were computed by the VP parser as the subiect and cases TH1, TH2, SUPPORTPTl, BALPT2. TH stands for cases ror Support Point, and Balance Point. The the spatial rela tion:. signifie.d by these cases: BALPT2 on/with/in his SUPPORTPTl. If these four

relation is completely defined. If object of the ACTIVE £om of the clause.

The conditions or rules For transforming these syntactic arguments into roles * semantic are as Collows: SBBJ A OBJ + mi +- SUBJ. TH ~ 4 OBJ SUBJ OBJ -+ TH2 + SUBJ + TH2 + OBJ For each ZOMP, NTH~ A ON A PSCT(C0MF) -+ TH1 +- COMP nlSUPPORTPT1 A IN v ONVWITH A PART(C0MP THL) + SUPPORTPTl + COMP dBALPT2 A ON A PART(C0MP TH2), -+ BALPT2 + COMP

T + PRINT (LIST "UNDEFINED COLON COW)

For the following two example sentences, the above rqles result iri the bindings (shown:

Ex 1 A c,lown balances a pedesta1.0~ his head on its side I I I I TI11 TH2 SUPPORTPTl BALPT2 Ex 2 A clown balances on z! pedestal on-its side on his hegd I I I i Additional modifiers may have been present as-in the example sentences:

A clown, on his hands balances a pedestal on his head, on its side beside a pole.

A ololn with a pole in his hands b'alances on a pedestal.. . The earlier action sf rhe preposition semantic functions will have reduced these additional 'Notes:' x -+~y x 4 y Ax F'(x) complements to no more than those ~bown in Edamples 1 and 2. X imp'lies Y SET x to y Not X Evaluate function F of X n( and V or " Quote Brief forns such as "A clown balances on hi$ hands" or "A clown holds a pole" 'result in inbomplete bindings from the rules of SUPPORTL. The legitimacy of suqh brief forms iequires a default logic that in the first case assumes that the Ground supports the clown-at a point called TOP of the ground. In the second case, the clovn.'s SWP~RTPT~ for the pole Is bound to hrs hands and the BALPTZ--for the pole-- is bound to the BOTTOH of the po le The verb "hold" puts a default value of "hands" on the structure it passes to SUPPORT^ according to the following definition: (HOLD (LAMBDA (ST) (PROG ( ) (PUT ST ''SUPPORTPT~ ''HANDS)

wm (SUPPOBT~ ~ ~ ST)) >I) The default logic af the verb seeks these values to bind them appropriately to any-empty case arguments. The more general default values of TOP as a missing SUPPQRTPTl and BOTTOM as a missing BALPT2 and the fact that the object on the bottom of the heap must be supported. by the GROUND are all supplied just prior to constructing a picture frame.

The result of SUPPORT1 is to create a process model of the fbllowing form:

(C i TOK balance, GLOBAL (...)-,INIT(...),INTER(...)

RESULT ( . . . ) ) The value of the attribute, GLOBAL is a quoted set of (PUT X Y Z) whrch Me true at all t imes in the model. INIT !is the set of relations true Bt the initial state of time 5n the model, INTER Ts those for the intermadiage states, and R~SULT is the set fbr the final state. When a functionWG for Pragmatics evaluates one of these attributes, the result is to evaluate these PUT functions to produce a semantic network representing the state of 32 affairs at a given instant of time. The semantic relations are translated to ATTACH 4-tuples which then generate a picture of the state. Successive pictures are obtained by calling PRAG repeatedly for INITial, INTERhediate, and RESULT states. For the examples of the SUPPORT1 verb, only the GLOBAL attribute is given values as f~llows: ci . . . ,"GLOBAL (LIST ("PUT mi "SUPPORT m2) ("PUT TH2 "SUPPORTBY TH1) ("PUT TH1 "sUPPO~PT SUPPORTPTl) ("PUT TH2 "BALPT BALPT2) ) Initial, Intermediate and Result states are null since the verb simply describes a static state.

The verb MOVE* is more,complex and more interesting. Let us assume as input the-sentence, I I A clown on his head ;ails frorn'Corno to Menaggio" Wheh the parser has completed its VP the semantic structure .1~ as follows: (abbteviated to the portion relevant to-this discussion.)

(Cl TOK CLOWN, BALPT HEADXY, SIZE 3)

(C3 TOK SAIL, SUBJ C1, COME'S (C4 C5), TENSE PAST)

(C4 TOK COMO, . . . ,PREP FROM) (C5 TOK KENAGGIQ, ..., PREP TO) A t this point VP calls'(Sh1L C3). (SAIL (LAMBDA (ST) (PROG ( )

(PUT ST l q "WATER) ~ (PUT ST "VEHICLE "BOAT) (RETURN (MOVE* s T) ) 1)) That is, SAIL implies a movement of*a boat on water and so passes thiS SAIL is defined as f~llows: ~ ~ ~ ~ Lnformetion to mVE* which may have to use it to bind lte case roles of 5EDIUM and VEHICLE which in fact at? not mentioned explicitly in the example sentence. MOVE* binds the arguments Agent, THeme, VEHICLe, - Source, Goal, and MEDiuhby sorting out the information contained in SUBJ, 0EU and COMPS by the following rules: ANIM (StJBJ) + A + SUBJ FORCE (SU3J) + 1 + SUBJ

VEHIC (SUBJ) -, VEHIC + StJBJ

S VMIC /\ mIC (ow) + WBIC + OBJ

MEDIUM (OBJ) + MED + OBJ

OBJ -+ TH + OBJ FOR EACH COhF

a MED A IN V ONLV THROUGH A MEDIM(CObfP) + MED + COMP

% VEHIC A IN V ON V WITH A VEHIC(COMP) + VEBIC + COMP

% S A FROM fi PUCE(C0MP) -+ S 4 COMP

G A TO 4 PLACE(COM2) -t G c COMP T + P P , ~ (LIST l r : COMP) ~ ~ ~ ~ ~ ~ ~ DEFAULT :

s VEHIC + VEHIC + (GET ST WHIG); % 6 -+ S + (MAKETOK "POINT)

.\I MED + MED + (GET ST MEDIUM) ; w G -+ G c (MAKETOK "POINT)

Thie definition of the canditione for MOVE* is at i l l incomplete except fox the verb "sail" and will be modified with further experience.

Haying bound the role varieblee, MOVE* creates a procese model by assigning to ST, gets of value8 for the attributee GLQBAL, INITlal, INTEBmediate, and,RBULT. 34 For GLOBAL conditions, (AND I (PUT S "SWPORT 1) (PUT MED "SUPPORT VEBIC) (PUT' I "SUPPORTBY S) ) (PUT VEELC "SUPPORTBY MED) (AND A TH (PUT A "LEFTOF TH) (PUT VEBIC "SUPPORT A) (PUT TH "RIGHT OF A)) (PUT A "SUPPORTBY VEZIIC) (AND A (PUT mnIc 1 1 A) ) ~ ~ (PUT ~ MED "LEFTOF ~ G) ~ ~ ~ (m TH (NULL A) (PUT VEHI C "SUPPORT TH) ) -(PUT MED "RIGBTOF S) For INITIAL, (PUT VEHIC ' 1 S) ~ ~ ~ ~ ~ ~ ~ For INT~~mediate? (REMPROP TJMIC '"RIGHTOF) (REMPRO? s "LEFTOF) (PUT VEHIC "BETWEEN (S G) ) Por RkSULT, (REMPROP VEHIC "BETWEEN) (PUT G "~IGHTOF VEHIC) (PUT VEHIC "LEFTOF G) Ffg. 3 shows theee states in the form of a process model, When this process model, C3, is evaluated, the function PRAG is called with the arguments C3 and either INIT, INTER, or RESULT. PRAG will first interpret the GLOBAL attribute causing the state represented on the property liste Tor Tokens of clown, boat, etc. to be changed. It will then make the changes indicated by the PUT8 which are additions , and the REMPROPs which are deletions. If PUG ie called three times in succession for INIT, INTER, and greeeion of the support and BOTTOMs RESULT, three euccessive sfatee are created to shaw the pro-

the process from etart to finieh. After PRAG has been called

points and balance pointa are all defaulted as neceeaary to TOPS

by the function that calls the GRAPHIOS system, This function I SWPORT INIT: PUT VEHIC "RIGHTOF S INTER: ~ R O VZHIC P RIGHTOF OF RESULT : PUT VEHIC LEFTO OF G Figure 3. PRocess Model For,MOVE* also establishes horizontal contact points for BETWEEN, RIGHTOF and LEFTOF. VI Semantics of Scenes

A scene is composed of a set of Pictures related to each other by adjacency and Support relacions including their poiats of contact. A picture is a LOGO display program that when called with a given start point and heading of the display turtle or cursor will construct a two dimensional line drawing. A square can be drawn by the following sequence of operations. (See Papert 1972.) PENDOWN, FORWARD 20, RIGHT 90, FORWARD 20, RIGHT 90,

FORWARD 20, RIGHT 90, FORWARD 20, RIGHT 90, PENUI?. The last ''FIGHT 90" restores the cursor to its original heading. FORWAEU and BACK axe vector making functions that draw a vect'or from the current xy point of the curser a given number of +its in the direction the cursor is aimed' The language uses functions with arguments and may create and call subroutines. Square may be defined as

SQUARE;SIZE: FORWARD :SIZE,. . . -.ETC. If a triangle has a l s~ been defined, we can then define:

H0USE:SIZE; SQUARE:SIZE; F0RWW:SIZE; TR1ANGLE:SIZE; It is the convenience and simpl~cityeof these LOGO conventi'ons that convinced me that drau3,ng pictures from sentences would not add any gteat complexity to a basic language analysis system.. LOGO offers many additional features as a language for teaching programming skills to non-mathematically oriented users and one of the most important of these may be as a parenthesisfree form of LISP. In our use of LOGO graphics, we-consider that a picture has a name, a program to praw it, a cursot startpoint~value, a head'ing, a size, a frame of minimum arid maximum X and Y coordinates, a center of gravity and coordinates associated with any points on it that we need to refer to, such as feet, hands, head, top, bottom, etc. CLOWN EQR (LAMBDA.() ...I SIZE 1 STARTPT (XY) HEADING NBR PFRAME (MIN X, MAX X, MIN Y, MAX Y) FEET a a

BOTTOM (=> All of the XY coordinates designated in a picture structure are relative (Xi) to the startpoint, heading and size. If we set the startpoint to a given value, say 500; 0; the clown w i l l be drawn from the bottom center of the screen. If we set HEADING to 90, it will be drawn on its side. 1f we change size to 2 each vector composing the picture w i l l be twice as long.

If we whsh to translate the clown to the right 50 units, 50 is added to the X coordinate of the startpoint. IF we wish to m6ve it up, a number is added to the Y coordinate of the startpoint. If we Wish to rota-te it onto its head with its head at 500,100 life is more difficult. We must use trigonometrikc functions to compute a heaaing value and a location of the startpoint that will achieve this result. A functipn called ORIENT* takes as arguments an object, i-ts balance point, and a reference point. (ORIENT* CLOWN, HEADXY , (500,100)) This function adjusts the startpoint and heading so that the head of the clown w i l l be at (500,100) with the center-of gravity above the point. Siinilar- adjustments are made to the PFRAME values to translate and rotate the imaginary picture frame defined by the XY extremals. To assemble a set of pictpres into la scene, the bottom pieture is assigned an XY s~tartpoint and heading. Each picture it supports is translated and rotated to result in adjustments to startpoint, heading and pframe values. Each picture beside it is s~ i la r ly adjusked until a scene is cgmpleted by accounting for all its pictures'. At tQis point, the scene is scaled to the size of the display screen, and the picture drawing programs are,executed.

The PFRAME concept developed by Gordon Novak and Mike Smith is very helpful as a computafional abbreviation Eor.fhe program that draws the picture. The PFRAME attribute has a minimum x, maximum x, minimum y, maximum y as four points that define a rectangle that surrounds the extreme points of the pictime, When the picture is programmed these are assigned by hand with reference to whatever startpoflt and heading were used. The picture as defined is taken as size 1. Whenever the picture is translated or rotated the values of PFEUME, STARTPT apd HEA~ING are adjusted accordingly. A s each pair of piccures are combined into a scene, a F FW is computed for the scene. The final PFRAME for the entire scene is adjdsted to the size of the screen w i th appropriate scalidg of the size values of its component pic turas. 39 A f'requent use of PFRAMES is to find default values for TOP, BOTTOM, LEFTS~DE and RIGHTSIDE as contact points between pairs of pictures . Dep'ailed descriptions of these processes are-not particularly relevant to this paper's goal of presentipg an easily computable syntactic-semantic scheme for subsets of English but w i l l be presented in forthcoming papers by Bennett-Novak and by Michael Smith. VII CONCLUDING DISCUSSTON In previous sections the terms "proceas madel", "skit", "~cene'~ and "pf rame1' have been wed to describe very llmited' structures of verb and noun semantics. This usage is in contrast to the much broader ideas associated with "scripts1', "f tames" etc. which ate typically used to describe worlda of vision ma belief system&. Example process models for "support" and~'@mve1' have been described and applied to the task of organizing images- into scenes. Nouns such as "clown" , "dock", "pedes tall', etc. have been represented as programe that construct line drawings. Adl\ectives have been used to communicate variations in eize, and adverbs to\ indicate angles. Other nouns, such as "top", "bottom", "edge" etc. are defined as functions that reference p/r ticular x-y coordinates of s picture.

Npuns such as I1 circu~", "party", "ballgame" etc. have not yet been attempted. They imply partially ordered sete of proceas models and are the most exciting next step in this research. More complex verbs like "return" or "make a roundtrip" imply a sequence of interacting proceas modele. Thus. "a clown sailed from the lighthouse to the dock and rethrned by bus" offers 40 interesting problems in discovering the arguments for MOVE*-return as well as in the design of a higher level process model whose intermediate conditions include the models of MOVE*-sail and MOVE*-return. We have also noticed that the semantic network that is produced as a result of semantic analysis can be seen as a problem graph by the functions that organize images and it is apparent that as these graphs come to contain larger numbers of images, it will be necessa'ry to d'etrelop graph searching etrategies along the lines of ordinav problem solvers. Our first experiment in this lihe will be to semanti~allp analyzeo the miseionariee and cannibals problem and illustrate the solution.

As it stands, the CLOWNS system has served as a vehicle for developing and expressing our ideas of how to construct a tightly tntegrated language processing system that provides a clearcut syntactic stage with coordinate semantic processing introduced to reduce ambiguity. Twd stages of semantic processing are apparent; the first is the use of prepositions and verbs to make explicit* the geometric relations of "support", "lef to£" etc . among the objects symbolized by the nouns ; the second is the transformation of these geometric relations into connected sets .of x-y coordinatee that can be displayed as a scene. Schank'~ notion of primitive actions is refle,cted in our approach to programming high level Verbs such a8 MOVE* to encompass the idea of mation carried in verbs such as "sail", "ride", etc. Yoadd ATN approach to syntactic analyais ie central to this system and in sharp contrast to the approach of Schank and Riesbkck who attempt to minimize formal syntactic processing. Our procees model reflects the ideas developed by Bendrix in his development of a logical structure 5sr English semantics. 41

The system is not li'mited to its prekent grammar nor to i ts preeent vocabulary of images. Picture programs to construct additional objects are easily cbnstructed and the semantic r~utihe6 for additional verbs and prepositions can be defined fo the eystern wfth relative ease. We hope in the near future to illustrate the following sentence: "One of the ffrst plant8 to appear bn a newly formed volcanic PsJsnd is the stately and graceful cocbnut palm." . This will involve programming the verbe, 11 appearw', "fgtm", "grow", and programming pictured of plantg, coconut palm and islands. Very interesting problems are apparent in understanding and representing the ideas of "first" and "new" as well a~, in the relation between "plant en and "coconut palms".

The system has been used successfully to communicate methods for natural language compu.ta#ion to graduate students and to undetgraduatey. It appears to have immediate possibilities for teaching the structure of English, for teaching precision of English expression, iind for teaching foreign languages through pictutes. Eventually 'it map be useful in codunction with very good graphic systems for generating animated illustration8 for picturable- text.

In my and CLOWNS sh~ws thk power and vaue of the mic,roworld approach to the study of Artificial Intelligence. By narrowing one's focus to a tiny world that can be completely described, onen can define a subset of ~n~ l i sh in great depth. This is in corrtrast to the study of text where the situations described are so complex as to forbid exhaustive analysis. The translation into a visualized microworld provides an immediate display in a two-dimensional language of the interpretations dictated by the -syntactic and semantic systems and thus a scientific measuring instrument for the qccuracy of t&e interpretation. VIII REFERENCES Robert P., "~orlcepts ic 11 Abelson, for Representing Mundane Reality Plans.

In Representation and Understanding: Studies in Comitive Science,

edited by D. Bobrow and A. Collins ~radedc Press. In Press. Badre, Negib A., "computer Learning from English Text." ~lectronics

Research Laboratory, College of Engineering, University of

California, Berkeley, 1972. Bobrow, D., and Collins, A,, Studies in Cognitive Scienck, Academic

Press, New York 1975. In Press. Bobrow, D.G. and Norman, D.A., "Some principles of cognitive systerna, I I

In Bobrow and Collins. Bruce, wrtram C., "A model for temporal references and its application

in a question answering program." ~r t if ic ia l Intelligence, 3 1972

pp 1-25. Charniak, Eugene C., "Toward a Model of Children's Story Comprehension."

A1 TR-266, MIT, Cambridge, Mass., 1972. Collins, q., and Wafnock, E., "Reasoning from Incomplete Knowledge. 11 In Bobrow and Collins. Fikes, R.E., & Nilsson, N. 3. "STRIPS: A new gpproach to the application

of theorem proving to problem sglving, 1 t Artificial

Intelligence Vol. 2 pp 189-208. Gridhman, R., Sager, . Raze, C. and Bookchin, B., "The Linguistic

String Parser." AFIPS, Conference Proceedings Vol. 42; MIPS Press,

Muatvale, N.J. 1973, pp. 427-434. Harris, Larry R., "A Model for ~daptive Problem Solving Applied to

Natural Language Acquisition." Thesis MSS, Department of Computer

Science, dornell University Ithaca, N.Y. 1972. Heidorq George E. -"Natural Language Inputs to a Simulatfon Progradng

System. " NPS-55W, ~Hyal Post Graduate Schoor, Monrerey, Calif.

1972. Hendrix, G., rel lid nary Consfructs $or the Mathematical Modelling of

English Meanings " Univers$ty of Texas, ~e~arthent of computer

Sciences, Working Draft, April 1974. (not for distribution) Hendrix, C.G., Thompson, Craig and Slocum, Jonathan.- I I Language Processing

via Canonical Verbs and Semantic Models, It Proc. 3rd Int. Jt,

Conference on Artif ic.ial .Iatelligante, Stanford Research InsLitute,

Mehlo park; Calif., 1973. Hobbs, Jerry R. "A Model for Natural Language ~emantics." Department

of Computer Science, Yale University Research Report 836, 1974. Matuszek, D., and Slocum, J., "An Implementation of the Augmented

Transition Network System of Woods." Department of Computer

Sciences University of Texas, Austin NL-9 2972. Minslcy , Marvin, , "A Framework for Representing Knowled$e, " In The n

Psycholo~y P of Computer Vis.ion, V edited by P. winst Winston, McGraw G Hill

1975. 5 %pert, S., "~efich-lng Children to be Mathematicians vs . Teaching About

Mathematics.'' lm; Int. J. Math. Educb. in Science 6 Tech., New Y~rk: Wiley & Sons, MIT, A. I. Memo # 249, July 1971. Rieebeck, C. K., "The Conceptual ailalyzer." In Schank, R. Conceptual

Inf ormatYon Proceesing. Rumelhart, David E, "Notes on a Schema for Stories. t I ,

In Bobrow and Collins. Schank, R.. & Jibelson, R. "Scripts, Plans and Knowledge. " JGS,

Yale U~iversity, 1975. Schank, Roger, Conceptual InIomtion Processinq, North-Holland

PublishAng Company 19 75 (In Ptess) . Scragg , Gteg W. ,"LUIGI: An -EngTish Question Answering Program. I'

Thesis MSS, AP & IS Dept., ~nidersit~ of California, San Diego

1973. Sikl6ssy, L. & Dreussi, J., "An Efficient Robot Planner that Generates i ts om Pr~cedurei;.'~ Proceedings 3rd. Iat. - Jt. Conf . on A. I., pp. 423-430. . Simmons, Robert F., "Semantic Networks: Their Computation and Use for

Understanding English Sentences:" In Computer Simulation of

Co~itivemProeesses, edited b$ Schanlc. R. and-Colby, K Prentice Hall, N.Y. 1973, . , Walker, Donald Em, "Automat'ed Language Processing," in Annual Review

of Information, Science and,Technolop;y Yol, 8, American Society

Information Scien~e, Waehington, D,C. 1973. Winograd, Terry, "Frame Representations and the ~eclarative/?rocedural Controversy. " In Bobrow and ~o'lline. Winograd, Terry, Underatanding Natural Language. New Yotk: Academic Prehs, Woods, w .A . , Natural # 2378, Woods, h. A , , Analysis," Cotmn. ACM, 13, Oct. 1970. 1972. Kaplan, R.A., & Naeh-Webber, B., he Lunar Sciences &nguage Information System: Final Report: BBN. Report June, 1972, Bolt, Beranek 8 Newman, Inc. Cambridge, Gss . 11 -- Transition Network Grammars for Natural Language APPENDIX fiFTER S0CE CONTROL FuhtTyo~S THF PR INT~UT SHOWS THE GRAMMAR, THE LFXICON, TbE FUNGTIO~S THIT DRAW PI~TURE~

9 THE SEMPNTIC FUkCTIOhS AsSOCTATEO WITH WORDS; THEN '

THE RdS IC GRBPHIC FUNCTTOhS APPRoxIMATYNG LOGC E~u IV -

ALENT+, AND FINALLY TkE DFEP. SVdhT IC FuNcTIO~S 'FOR COVBTNYNB AND ASSWBLT~G DDA~J\NGS INTO SCENES.

TPE PROGRAM IS IN UTLTSP FnR ~0: EQUIPMENT 4ND-Tq WR ITTE~ TC INTFRF~cF WITH ah IMLAc ISP PLAY.

TH IS TS THE I;ET OF CO ~ TD ~ FLJNCIIONS~ L DRAW, PR4O ETc~

ClRPW ~AKES THF sENTF~CE as N o LATER PNPGI PREPRAG

HAKE SFMANTIC AFT ~QQK TO RFPRFSE~T THF MEPI~I~G OF ,

SENTFN~E PNC CdCL THE CEFP SEMAhT7C F IJ~~CT IONS 10

(fC(bAMBDA(fT1 Sf ) )

+A -DVMMY FUhc~1Oh FOR THF VFRR

(GEToK {LAMnOh (ST PR6P.) ((3~7 (GFT-ST =OK) PHUP) ) I

+AN I'NnIAECt GET FUNCT IO~ I~ (DQPWPTX (LACROP CTOKS I 1PRoG (1 ( L I ~ T I (YAKFAR) ~C~VPICS) +SEPARATE TOM TNTO !TOUS ~NP NTCKS:TO~SA (SEPTQKS (uwqni ( ) (PRC~; rTw51

(c.ETQ TUS TcKS) (sETQ TOKF ~ IL ) A (cOkO( (aF? (CAP TKS) FTFNSE) (sETQ vTOKS (CONG

VTOKY))

( (GEp,QglC P TKS) =PT.cT) (qETQ TOKS (COhs (CAH TcS I-T~rq) 1 ) (cO~~D ( SET.^^;^ tk9 SKCP TKS)J~(C,Q P) )

(1 ( ~FTLP NIL) ~ 1 THF RAW fT + (CAP TKS) +APPLIES THE PROCESS POOFC OF A #ERB TO 178 ARGUMENTS

PROP IS INIT, TN'I'ERv REsI~IT 4 (PRAQ (LAMBDA (ST 'PHU'P) (F'RW (0 L)

( ~ 0 ( (NU1 ~ 0 L ~SETTJ G (O f t $Th PR~P) ) 1 (RETURN NIL) ) A (EVAL (CAR G ) )

(cOND~~SET~ 6(CDR 0)) (80 A ) 1 ) 1 ) ) yP1) ) ~P2)h) I MOD) (LIST *) ) ) (PP(CAT PREP(NCT(GET(NEXT) EV))

(SETR PPEP (APPE~DIGFTR PREP) (LIFT * ) ) I (TO PP) )

(PUSM NP (GETR PREP) (PUT 8 ',PREP (GFT'R PAEP) 1 (HOP PP1) 1 ) (PPI (TsT TPPV (GETR VCO~;T ,Q~L)

(sETR VcOhTROL hqL)

(SETR HD 9) (HOP'] PP?) 1

(TST TPP~ (sETR *) J(P~EP-WATCH (COR GCSTI ) ) (SUF I n (To ~132) ) (PP~(PoP(GE:TR PO) (OR(SEf9 DPEP ~JTL) T) 1 ) (VfitCAT bU$ ~ h C (SETP f AUK [&PPEN~(GEJA AUX) (LIST *I 1 )

(LIFTR nL'X(GETC7 1 vG) 1 (CAT AOVBac;~TC(SETR VM(>T)(APP€NC(GETR VMO~ ) tbfqT + ) ) I

IT0 VG) )

(CAT V T (HOP VV '~ ')

(T?? VAUX (-GETR PUX )

(SETR V (LAST(GETR Q~JX ) ) )

(5ETR HP(w~KE~OK(GETF? V ) ) 1

(~ETQ GL ~T (CONS (Gmn V) GCST)) wvl HOP VO l ) 1 ) (TST VV T {SET!? V 9) (sFTR HO (MnKETQK

(SETQ bLfT[CbhS fll Sf)) (TO, VGlll 1 ) (vG~ (CPT AnV@ T(SETR VMO~ (APPE~~ (GFT~ vMOD) (~7S f * ) I )

(70 Vf l1))

(TST OK~OR (A~D (SFTQ J (GETR AUX) (sFTR TENSE (PET (CAP 3) ETrNSE) 1 1 (SETR TFNSE{GFT(GETR V 1 :TEN$€) 1 i?)

(PUT (GET P HD) STENSF IGETR TEWFF) )

(PUT(GETR WD) EAIJX (SFTP AUK))

( I IFTQ AUX (GET'R AIJX) )

(PUT tc~T14 HG) ZVMCIU (GFTR VMon))

(HOB V63) 1 ) (V02(POP (GFTR HU) T 1 ("P(PUSH VO SWTC (SEW V 9) (TT) VP1) 1

(TsT TbP1 NO toft (GETR ncl.) (BET (LAST (6ETR 4UXf 9 50~ 1 )

IGET(GET(QFTR V ) f70K)EFD))

(sETR PA+* T) t$ETR QRJ (GETR $UBJ) 1

ISETR SURJ ~ T L ~HOP-VPZ)) ) usr TVPZ T~WQP VP~ ) 1 ) (Vp2 (~ISB PP (&hD (GETA PAW) (GET * %BY) (SENOR' VcdhTRo~ T)#

(SET!? SUB; *) (PUT (GETR V ) 1094 (GETS ORJ)

(PUT NETR V) ZSURJ (GET? SUBJ) IT0 V P ~ j )

(PUSH DCLAUSE (SE~OR ncL TI (TO v~z i, ,

(POPtGETR V) (PUT(GE:TR V) :S[JPJ lGETR SURJ)) 1 ) (DcLAUSE (PUSH FP (GET :PREP) ~SETR Hn a) (TO *) D4) (Push RELCQNJ (CAT ~RCQNJ) (SETR * hk (TO 04 ) ) (CAT FIPRON T(SETR ~UAJ (AhTEC GLST) 1

(SENDR €0) SUBj (GETR SUBJ)) (TO 011) (CAT V(QR(GETF (RFTF ING)) (H~P 02))

(CAT PREP (AND (GETF TO) (GET (hiEXT) =v) (SCPNXT~) (HOP 02)) 1 (D~TST 02 T (sETR.~UBJ(VRMATCH 6 GLST))

(SENOR SUf3JtSETR 9UBJ) ) (HOP 021 (n21 (PIJS~ VP (SENDFI DCL T) (SETR HE a) (MOP {Dl (PU$H PRONCLAUSE f (HOP t73) 1 ) C-a3(fsf ~ ~ ~ (G * E SuBJ, TR (SFTR HD *I ( ~G<T ZTOK) 9) +SFMANTICS OF VERB&

(PUT (GFTR sURJ) SqMOD (CONS 9 (GET IGETR SUB J) ZSMnn) )

(TO C4) 1 1TST 7031 T (fET(3 .HOLD (CONS * CIOLD) ) (TO 04) 1 1 tD&(POP(GETR HC) T ) ) 03) 1 ) (PFIO~CCAUSE (PUSH,VP (SEUPR DCL. T) (SPTR HQ

(PUT .a 5slJaJ (GETA SUf3.j) ) (70 PR3) 1

(PUSH NP T (SETR OFJ (GF-TR SUBJ) ) I s ~ ~ SUPJ R a)

[To,PRl! 1 ) (Pql !PUSH DCLP~LSE T (SE~DR neb T) (QETQ D 9)

~SFTR DCL T ) (rn PRI) * ) (PUSP VG T(SETR HO +, (PUT SSUBJ (GpTR SlJBj))

(PUT * ZOsj [GFTP 0QJ))flo PR2) ) ) fPR2 (PUSH vDCt&LSE.

(T$T'TPR?. (TO (RR3 (PO? (G&?R PD1 (RELCONJ~CAT RCOHJ *) RCONJ *).(TO P I ) I (RI (PUSH DCLPUSE T (sETR rn (H~F ~21 ) (PUSH C ~USE SNfC * (SETR ~b 6 ) [HOP R2) I-) (Rz(POP(CETR-HC) (PUT EaCnNJ (oETR RcoNJI) ) ) T (T(? PQ?) 1 PR3) 1 ) T) 1 ShTC (SFTR ) STRLJCTIJRE EXCEPT THAT (GET ITHE EABTI RETURNS STWE& (LFXICBN f ( (*TYF ART (DET OFF) (NBR (qthlG PL) 1 ) (A Afff (DET INCEF) (NBR (SJNGII) (AN ART (DEf rhDEF) (?BR (sTNG) I ) (BIG AnJ (SIZE 7) (CLASS SIZE) (LARGE ADJ (~TZE 6) (CLPS~ sIZF) ) (LTTTLE ADLJ,(sIZE 3) ~CLA 'FS SIZE) J (SMALL AOJ (q12E 4 ) (CLAS'S ~ 7 2 ~ (1s bUx (TE~SE PRES)(BE 7)) (WbS ~ .JX (TFN~E PASTI (@€ 7, ) ($ERE IUX (TFNSE PAST) IBF T) ('~IBR (PL) ) ) (9Y PREP (W T I ) (BESIDE PREP (CAhON RIGHTOF)) (to IN\ PRFP (TO 7)) ( PREP (CAhlqh 01\41 I (ON PREP (ckkdh OM) I (WyTH PPEP~~ - (cA~O~ ON) ) {FaOQ PREP (~nhoh FROP)) (THPO~QH PREP. ( MEISIUC T ) 9 (ACROSS PRFP (PEDIUM T ) 1 (CLOWN N (NBR SING) (FAhPs TI (HE~Q T ) (FEET TI (PER5 T) (PICT TI (P.~$IM f) (dRr T) (ARMS 7 ) (NBR S T ~P T I (BPS€ f) ) (PEDESTAL N ING ) ( P ICT fl-) (70 PREP (G -T I ) ~ R Q P PREP (7 T I ) (HFAD r\l (NRR SING) tP4FT t-) ) (NOSE N (NYR ~INC) ~ P ~ R 7)) T t ~ o ~ N k (PIC7 f) (NRR SING)) (HEAO M (NRR $ING) (PPRT 7 ) ) (PFET N (NBR PL 1 (PART 7) ). (ARF N (~BP 's I~G (PART ) T) ) (ARMS rd (NBR PL) (PART t)l (TOP 14'(h&R ~1,hG) (PART T, (WEL 1)) (RAW r\r -(NHR ~ING) WPLRI PI (wR'FL TI) (SIDE N (NBR SING) (PART T)'(NRFL T ) ) (BALB~CE v (TF~SE PRES) (JNF 1) (PFF)~S (ON WIT). IN)) 1 (RALANCE3 V (TENSE, PWES,) cpQEP5. (ON WITH IN) 1 (BAL6NCILhG V (JE~SE PREY) (1bIG T) (PREP5 (ON WITC WITH IF])). IN) ) 1 (Ba~eNcEd v (TE~~SE P~ST (EO ) T) f) (PPFPS (ON J (SUPPOR'J V ((TfhqE PRES) (JNF (PREPS (ON WITH) ) 1 (S IJPPOC~~~ v ' (TENSE PRES) (PREPS (-ON HITHI ) (SFJPPOFITED V (7EhSE PAST) (FD T I f (PREPS (ON W/fTt-l)) 1 ($UPPORTIVB v~-(TENSE. PAES) (ING (PREPS (ON myTu) ) (SA~L ING Y (TchSE PRESl (TNrj TI (oREpS (TO FROH TPRO~J~H ACROSS IN ) ) 1 tsnrlEn v-* [(TEN~F PASTI +n T) (PRFPS (TO FROM ITHRCIUGH ACROSS TY) 1 [ S% ~VT~~ PHLLI :SF (P~FPS (TO FROM THRoUOH ACQQS 4CR0+9) ) ) S P ~ ~ TN 1 (SAIL. V (TE~SF PRES) (PREPS (TO FPOM THROUG~ ACHOSS ~h l ) ) ) IHaLfi V (TFNFE PPE~ ) (IhF T I (PREP$ (IN W ITH ) ) ) IHOLDS V (TE~CE PFEs) (PRFBs (IN k17t-i) (IN 1 ) (HELD v YTFIU~F PAST) (EC TI ~PRFPS W ITH))) (WOLDING V ITEhSE PPESI (TVG T) (PREPS ( IN WXTtk))) (MHICHSRPRO~ (S~FG T) ( A ~ Q ts1brG PI.) 1 ) (rHAT' RPRO~ I (NI?'FT :S.T'hG PI.) ) 1 [WHO RPRO~ t6BR (SING PL))(PEQT TI) (IT PRON (NOR (SING11 ) ( ITS PPRON (WAF (SING 1 ) ) 4HTS PPRII)V (hRR (SXNG) 1 (PEPS T I ) (HFR PPAQN (NRR (SING) loYQ5 TI ! ) (HF P.RQN ~NRR (rilbNG,) ) (PFRs 11 (SHF PROk 1NRR (S ING ) ) (PFR~ T j ) ) ) {THEY PRQN (NPR (PL)) (PERS X I ) (wpl~E R~ONJ (TIME SANE)) (BEFORE RCOkj (TIME F IR~T~ ) tPOIb7 N (LQC T I (PXcT f 1 I (WINO N tNRR sJMG) (PICT T ) (FORCE T ) ) (BOAT M INQR SING) (PIC7 T) CVERIC 7) (~~ED-TUM WATFR) tPaCK N (NBP sZNG) ('PICT T I 1 ~L~GHTHOUSF w (NBR'SZNG) ~PTCT T ) ) WATER N (NBR SJ~UO) {P ICT ,T) (MEDsu'M T) [DVEHIC BOAT)) (AFTER RCPNJ (T INE LATER) ) tsE~o TORS NIL) (SETQ WB NIL') (SE~Q FCC NTL) (DEFINE Z [ +THE FOLLOWING FUNCflQhS ~'EFIYE THE PICTURES USE0 BY THE sYcTEM 4 C DRAW A PEDESTAL 4 (PFDESTAL (LAMEOA (SIZE) (PRUcJ 0 (PUSHSCALE. SIZE)

~PENDOW~J).

(VECT 2n 2q) (PPGnT 90) (FOQW 30) (VFCT 20 20)

(BACK 70) (LEFT 9Q)

( PFNIJP 1

{POqSCALE) I.? +D~PW A POLE* (P~LE ~LAMBD~ (SIZE') (PRCG / I (PUSYSCALE SIZE) (PE~DOWN,) (FOHW 10) (SACK 5 ) lPIGHT 90) (FORW 50)

(LEFT 90) (FQRW 5) (R~CK 10) (PENUP) (PQPSCALF') ) ) z & IM1,TIAtIZE STUFF FOR 0 CLOww AND 0 PEDEST4L. 4 (CLOwNlNXT (L#NBOA (p~ll)G (PUlfRFkS E(P(31h-T STARTFT (0 0) ~TARTOQTENT O

PFR4ME (O a o n, PSCALE 1 ~RIWPFOG PO~NT CG 1 )

(PUTRECS SiCtQkN Sf APTPT (14 Q) S~T~RTORXENT 0 PFAAPE (0 50 (1 68)' PSCPLF, 1 BOTTOM (25 0) TOP lp5 68)

RFOOT (14 0) LFOOT (36 0) FEET (-25 0)

DRAWPROG CLOkN

RaRP (0 34) L4RM (50 34) HF'AD (25 68)

HANDS (25, 34) ARM ( 0 34) ARM$ [ 25 -74) CG (25 76) ) 1 (PUTRELS.Z(POLE STARTPT 10 (i 0) ST~RT~R IE~T r) PFRAPE (-8 60 o 10) PSCPLF: 1 ROTTOM (30 4.5) TOP '(30 5.5) RASE (30 4.5) CO (70 5) T IP tr) 5) DRPWPROG POLE)) ~PVTPELS I (PEDESTAL STAPTPT ,6) STARTORIENT 0

PFRAWE 40 70 o 20) Psca~E 1 BOTTOM (0 35) T ~ P (35 20)

B4SE (35 a) CG (35 8) ~AAVROC PEDESTAL 1 )

(PYTRELS E (BQBT STARTPT (0 0) STPRTOQIENT 0

PFRAME (0 150 0 20) PSCAtE 1 ~IRAWPROG BOAT

ROfTOw (75 0) TOP (75 L n ~ LEFTSIDE (0 16) RIGHISIDE (150 in)

CGn (75 10) 1 ) (PUTRELS ~ (WATCR STARTPT (n O) STARTORTENT o

PFR~ME (0 500.0 5) PSCACF 1 ORdWPROG WATER

BOTTOM (250 0) TOP (259 5) LEFTSIDE (0 3) RIOHTSI~E (500 9)

CG (250 4t 1) (PIJTRELS f (L IQ~TwOUSE STARTPT (0- 0) STARTORIENT 0 PPRAPE (0 100 8, 350) PSCaLF. I, DRAWROG L T ~ ~ ~ ) ~O ~ . S € ROTTOM (50 0) TOP (50 350) LEFTSIDE (0 175) RIQuTSIDE (100 175)

cn 156 175) 1) 4 A PITIFUL EXCUSE F'UR P THF wITARD OF 02, 4 CbOkN (LAMBDA (SIZE)

(PUSHSCALE t1ZE)

7PENDOhN)

(RECT 2 8) (PQS 2 4)

(RFCT 28 18) (POS 28

(RECT a 101 ~PQS ~ s

tRECT la 4) (POS 50

(V ~ c t 8 6 ) (vECT

(PnS -12 -14) (vECT

(LEFT 90) (FORM 2) (LEFT 90) (FoRW 41

(VECTI 12 1 ~ (?as ) ~ o la) I\)ECT -12 12

(FORM 4) (cFFT 905 (FOaW 2) 11 EFT 901

(VFCT 14 -14) ($05 -48 -?O) (?€NIP

(P0PtCAtE)

) 1 ) (WATER(LA~BQA (SIZE) (P'Rco t z (PUSHSCALE ST2F) (PENOOWN)(VECT 10 125) (VFCT -10 l?S)(VF.CT 0 1 2 5 ) ( v ~ ~T (PFNUP) 1 ) (LTGPJTHOUSE (L~VPDA (tI-ZFI

(PROG ( (P~SWSC ILE S'IZE) (PENOOWN) (RIGHT 90) (FORW IQO) tVFCf -20- -250) (LEFT 90) (FoRh 50) (LEFT SO) (VECT 75 lb ) !VECT' 25 -10) (LEFT 90) (FORW 40)(PFNIJP) (VECT ,O 20) (PE~OO~N).(VECT -50 -90) (PE~cIP) (V'FCT 25 O[ (?FNOOWN) (VEC7' 0 90 ) (PENUP) (VE~T -50 d ) (PENOCWN) (VECT 50 -Qr)) (PENUP) (VECT fi 20) (PEhaOWN3 (VECT 0 50) (VFCT 250 201(RIGHT '18fl)fP~NUP) I ) ) (DOCK (LAPBOA (SIZE 1 WRQG ( fPUsHc;CALE c;t ZE 1(PENDQMN) IFQRk 30) (RI.GI.'T 9V) (FORM 104) (RIGHT 90).(FORM 30) (RIGHT BOI.(FORW 15). (RIGHT 90) (FOR! 20) (LEF~ 90) FOR^ 55) (LEFT 90) (FORM -20) (BIGHT lea) (pehrlP> ) 1 1 CCnNPlc MOPE LIKE THE TIN WOODMAN OF (PRQG 0

(nECT 18 4) (POT; 18 d2)

6) rWCT 4 6 160s 4 -2)

2 81 t~m r 2 a) 2 01

(LEFT.9o) (FQRW 1) tP1GHT 96) 6 ) (I-EFT 90) (Fn~lrl 1) (RIGHT 90) -14 -14) (LEFT pn) (FORM 2) (LEFT 9nl (RIGFT 90) (FORM 2, (RJGHT 90) -10 125) OF c~MONXCAL CORMS WHICH ARE THEMSELVES FuNC~fflhS c (WFINE 5( LRXGHTQ~ LAWRDA (:hl 412)

~c~ND ( (A~D (~ET S?I[CT) 'N -~ (GFT hZ ZPICT))

CPUT' ST 3AIGHTdF -fO~l) (PUT TOK1 ZL~FTCF ST).) (7 NIL) 1 1 ) IFROP(LA~BOA(NI h2) ~ I L ) ) (TO (LAMBDA (Nl h2) kIL) I ~LEFT~F(LAMBDA (M I N2) ~R IGYTOF NZ N1) ) D (REs~DE(LA~BDA (Yl NZ!l (RIGHTOF Ni N2) 1 ) (HOLDS tL9H0Ot! (ST) (HOLD ST) ~HELD(LAVBDA(ST) (HOLD ST) ) ) t~n~n I~e~~awpgncsT (HOLD ) ST) ) I (HOLn (LAMBDA (ST 1

(PROG E) [PUT ST* ~sUPPORTPT~ ~UANDS) (RETURN(SV~'PORT~ ST ) ) 1 ) 1 ('sALCINCE l t4P~nA (Sf 1st) 1 (SUPPnpTl ST) ) 1 {RAt&NCEs CL~PRDA ILAMROA (SLPpnRTl ST) ) I U~A~,ANCEB {ST)-(SI!?PORT 1 ST 1 ) 1 (P~L~NG~~G IL~MEDA (ST) SUPPORT^ 5T) ) ) ! p S ~ ~ (LAIROA ~ o ~ T (ST) (SIIPPclRTl ST) ) ~S@PORTS (LAYRCA-(ST) ~SL IPP~RT~ ST) 1 ) (SIJPPORTED (LAM~DP (ST) (SUPPORTI' ST\ I (SUPPOQ~'XNG(CANRDAIST) (SIJPPORTX ST) (BacaNcE (La~~oa (ST) (SUPPQRT~ ST) 1 )(BALANCES (L~MRCA (Sf 1 (SUPPORT1 ST) 1') (PhLbNcXhG ~LA~QDA (St) (SUPP~RTI qf ' 1 ) +ALWAY$ RETURNS TRUE* (PUTWO~~S ~C~vat csrl ,a (PROG r ,J)

(CQNQ(~NULL(SETQ JtCjEt FT ZMOD))) ~RETORIU -ST) 11 e (CONO ( (NULL J) (RETURN st) )

(SETQ K (GET (CAR J) 3C1.45S) S

(PUT ST K (BET(CAR J) K ) )

~ E TQ J~CDR J)] (GO R ) (LAST (L.A*QDL (LST (CAR (R~vFRSE LST).) ) ) &"THIS IS A -STATIC €Tern+ VERB THAT IS THE C~NON ICAL FORM FOR 5UPPr)RT B4LbFCEv HOLn (SUPPORT~-(CPMPOA (ST) (PPnr: (511~~ oeJ .?Man woo THI T H ~

BA-LPT 1" 8AI PT 2 SUPPOPT9Tl SUPPQRTPTZ J TOK COMP )

CVSFT ST)

(cOND ( (A ~B SU83 O&$) (cETQ .TH1 SU8J) (SET@ ' TH ~ OBJ) )

(SURJ(SFTQ 'fp2 $URJ) (,OBJ (sETQ rTH2 CRJ) ) 1 ICOND((NU'LL VYOD I~ IL )

( (SET~J 4 (CAR Vw0nj 1 (PUT TH2

(GET J =CLASS) (B€T J (BET' J :CLASS)

(SETU VMO ~ (cDR VYOD) l (no V I ) I ) (CONO ( (NULL P~OO ) IGO O~FPULT) I J

(SUB CONP(CAR PuOb)) (SETQ PM~D(cOH PMOO))

( CbNC (ISETC PREP I BET ~OMP ?PREP) 1 SETa PREP t CAR PQEP) 1 ) I

(SETB TQK(GET C 'OM~ 5TOK) 1 ( ~ 0 ( (~hn ~ 0 (NULL TH1) (OFT TOK FPICTJ (MEMBER PREP (LIST SON EIN) ) 1

(sETG TH~ .(SQMP~ 1

( 4aNO CR,J (NULL SUPPORTPT~) (MFWQER PREP (LIST = - IN Znhi SM ITH) ) Vl PI

( (WO ALL OBJ) (N~~LL RALPTL) (McMBER PREP (LIST :ON ZwITH) )

(SETTS BALPT~CGETQU T H ~ TOR-)) )

(PUT TP2 ZRntPT BALPPZ) )

( (AND (lkULL RPLPTI) (MEMRFA PREP (LIST EON IRY ) )

(SETO BALPT~(GETPK Tw1 TOK)) )

(,PUT 1 ~R~LPT BALPT * 1 ) . )

(T~PRINT (CONS E~~NACCQUNTF ~ .~ ~ 6 t 0 ~ )COPP : ) ) 1 ) (GO P l ) DEFAtJh T

(CONO ( (Ahn TH1 fH2) (PIJT THI ~SVPPORT TH~ )

rpyT T H ~ =SUPPORTBY Tnlj 1 )

(AULL SCJPPORTPTL) (sEJQ TIJPPORTPT 1 (GET ST ZS~ IPP~R~ PTI) )

(SEW SUPP~RTPT~(GETQK Th1 SUPPORTP~ I))

(PUT h 1 FsIIPP~RTPT SUPPORTPT~-) ) ) +NOTE THIS XS A STATE 'VE~R 50 NCJ PROCF~S MOUE-t,. IS CON~TRVCTF~~ 1-1 (VSE?'(LAMBOP (57) (PRQG 0

(c;ETQ

(P'T'IQ

(sETQ

(sETQ ~cONO ( SUR J (GET S t Z~ IJRJ) 1 OqJ (GET ST 3n~,1) 1 PwbC (GET ST =pvOD) 1 VMOD (GET ST 3VMOD) (sA.1~ (cA'FBDA ($7) (PRQG (1 (RUT ST ZMFDTUF 5w4TEFVl(PUT Sf FVFHIC ?BOAT) (RFTUHN(pQVE* ST)) 1 ) ) (SAILS tLAMREa ($TI ($AI-L ST) ) ) (SAXL$O(LAMB~A(ST) (SAIL qT) ) ) (SAXLING tLAtd~~A(s7) (SATL 511 ') 1 IMOVE~ (LnMsn~ (ST) (PROG C~UBJ ORJ COMP COWS A TH PMon

I VEHIC MEQIuM S G J) +SET SU~ J ineJ COPPS N ITH VSET 4 (VSE7 ST) (c~No (GET~K ,~ 9URJ EFORCE) (sf7n

( (GE~OK~ SLRJ fAhIY) (SFTO

( (QETQK sUBJ EVEHIC) (WTO (CoNoI (A&D (N ~ T VEHIC) (GFTOK

('(GETOR ORJ ZMEOIl,M) (c;ETq

(OBJ (7Efr3 1I.c 'QSJ) 1 1 &FOR EVERY COMPLEMENT 4 'PI [cOND(: (NUI, !! PP80) (GO- ~EFAUI,T) 1 1-70 COMP ( AR PMOC))

(5ET.Q PREP (CAR (SET ~OMP =PRFP) )

cwrapwo (RFT COMP ZTOK~ )

(CC?Nc(tAhD(h\JLL VEHIC) (MFYqER PPEP (LTsT Z IN ZON))

(OFT NWO SVEFLC) I (cET~J- VEHIC CON?) ( (AhU (?~uI.L vEDILJM) t MEVREG? PREP (I , 151 %ON ETwROUQH f ACMnCjS ZIW) I (GFT NHDQEMF~TOM) 1 (SETQ MFDIUM €OE49) )

( (AND (NULL S) (MEMBER PREP (LIST ZFPQM 30bT Z~EF ) )

(CET hIW0 ZPICT) ) TSC78 -S CQVPJ ( ( (MEMBEo PREP (LIST 30 ) AhD (NIJLL .GI '~F%R) )

(GET NHD ZP IGT)) (SETQ G COYPI)

IT (PRT-P~T (LIST 4Uk'llE~tr~EO; cOMP) 1 ) 1 ~CON~((SFTQ PMOD (CDR PMnn)) (('30 PI) 1 ) OEFAIJLT 4 i LOOK ON hPS FOR VEHIC* h-'EDIUM, S n,(NOT DOWE YET)

SUB 11 ) A . SU~J) )

vEHIC SUB J) )

J ~VEHTC ) ) ?SETO VEHIc ORJ)

WEFIUY 0RJ) ) 53 2 3 4 5

LOOK -ON VFj ST TO SEEA TF -V&HIc AND MEDIUM 'FAVF BEEN PASSFn UP

LOOK IN DIcTTONARY FOR ~IORHAL MEDIUM UEHIC GIYFN ONF

DFFAULT $ Akn G TO'LEF-T AN^) -RIGHT SCREEN DEFAULTS 70 TOP? BQTT~M t d l_E~Tr AHt7 RIGHTSICIF OCCIJR IN MAKEAR AND COMPICS ' JI (COND ( (AhD (NULL vE-HIC) (SFTO J (OFT ST EvEHIC) 1

(SETC VEwTC (MhKFTOK J) ) ) 1, (CnNn((AhD(kul..~ CEDILC) (cFTO j(nET ST EM~QIUY)))

(SETQ MEDIUM (NAKFTflK J) ) 1 ) (COND((NULL'$) (sETO S (P~K~TOK %POINT)) 1 ) ~CCLNC(~~~ULL GIISETQ GWAKETOK IPCT'NT)) ) ) (c~Nf i( (Ah0 -wE~IUP (NLLL vFYXC) (c;ETQ 3 (QETOK WEDTUM ~DV-EHI(~.) ) 1

(SETG VEHIC (VAKETON $1 ) 1 ) (CONE ( (Ah0 VEHIC (NULL MFDILIM) ($ETQ J (BETOK' VEHTC EDMEDIUM) ) 1

(SETC 4EDTUM (,PAHFtr)W J) ) 1 +PROCESS, MQDEI.

PU7SA GLnRPL COhrOIT'Ir)NT ON 5EMANTTC NET* PUTS INITIAL*

~NTERMEo I~TE 4N0 HESULT c~NDITJONS ON ST WHERE PREPRAO ANn PRAG CAN ~RTNC THFW ORTOTME NVT TO CoPPOSE n PICTURE 4 GLOB~C (Ah30 [AND AND (AND (PUT (PUT (PUT (PIJT INIT WUT INTER (PIIT ST ZINTFR(LIST(LIST =QEMpRnP VEMIc ~R IG~TOF ) ) ) RESULT (PIJT ST ~RES IJLT~LXST~~L IST =PUT vEH.1C LEFTO OF G) ) ) (BFTURN Sf) 1 ) ) +HERE IS THE PROCRUSTEAN PFD FOR PREPQ~ITIONE 4 (WITW (LAPBOA (Nl h2)

(CONC((N!JLL(SET h l ZPICT))NTl.)

( (PUT~TOK~ ESIIPPCIRT ST) (PUT ST :SUPPORTRY ~ 0 ~ 1 ) ) (1 NTLH ) ) (ON (hArrlBOA'(b) h2)

(CBND ( [NOT (EFT N l 3PICT) )NIL)

( ( ~ ~ (S F TC J(GEf h1 N~))-(GFT TOY). E$~UPPCRT))

(PUT T0K1 ~F IJ~POQ~PT J) )

(J(PU'I .TOKl ZBALPT 2.))

((GET h2 3PICT) (QP~~G~ (P IJT ST.SSCIPPOF?T TflK1)

(PUT T0~1 SSUPPCRTRY ST) ) ( f ~ T L ) > 1 I (PUT ~s~PQORT 1) (PUT I EsUPP~)RTE~Y S) A tk fi SLEFTCF TW (PUT TH EQIGHTOF f l ) A (PUT vFr.Ie ES~PPORT A) (PUT A =~UPPORTEY !IEHIc) TW (NULL 4 ) (PUT VEHTC ZSIJP"PCRT TH) (PUT TH =SUPPORTBY -* VFWIC) 1 VEH~C EAROVE MEClbM) MEDIUM ZAELOJ, VEWIC) MEOLUY 5LEFTOF G ) (PIIT 6a :RIGHTOF *EI)IUM) MEDIUM :RIGHTOF'S) (PUT S ZI EFTOF MEDIUM) ST SINIT (LISTlLZST =RFMPRflP VEHIC VEt41c :LEFTOF) (LIS~ ZPIJT ZRTGHTCF 5 ) ) 1 PREPOSITIONS Akb THEIR APRUMENT!?~ TO ~ETERM~NE WHICH WORD RFsT' QUALJFIF~ AS THE FEA~) THAT -1s TO RE t.300IpIEQ JI +(P CAND N) 15 THE CALL WHTCH EVPLS* P WITH tnE ARGUMENTS CAN0 AN0 Ne ~ k f 9 MnDE 1 ALS~~~ IJSED Tc) CALL A VERB IN THE G~?AMM.AP~ (PREPMATCH (LAMRO~ (ST LST) (PPOr? (N CANn 0 TOK1 TOM21

(cOND([SE~TQ., P(GET ST ?PREP)) (SETQ P(CAQ P I ) I )

t SETB N (OFT ST =TQK) ) P (cOND ( (NULL LST) (RETUQN NIL) I

~sETQ C~hn (CAR LsI) )

(SETP ToKI,(C-AR(GFT Ca 'hl~ :UjI)r)

R (~060'( (ANC (GET ~bk 'n =v) (WEMBER P (GET CAhn ?PREPS) 1

IRETURN (PUT TOU ~ ~PMOD (CONS sf (GET TOul 5~~00) ) ) )

( (EG Sf TCKltl (sETC " r~1 (CAoR (GET CAN0 3L/I) ) (GO R)

( (P (sVC CahO N) CfiEtll~h! 70~1 1 ) &DO SEMANTICS OF PRFP.L (f tST(CDA I CT I ) (Gn A ) 1 ) (UNHOLD CLAMRnA () (PHOO ( J) A ~CONO((NIJLL, POLO) (RETU~N @XI,))

((GETKAR HOLD) EDREP) (GQ PI))

( (N1Jl.I- (cFT (CAR FOl-h) EsU~ J) ) (PIIT .(CAR HOI-Cl ZcIJRJ

(GFtP-?SURJ) +DO VB SEMART~CS~

(-(=.T(CAR HOLr)) ZTQK) (CAR HOLD))-(QO P2) 1

( (hULL (GET (CAR hCILn) ZQRJ) 1 (PUT (C4R HCI,O) EOr.1 J (GETP =sIJHJ)) cD0 vF3 SEMANTICS4 Jd

( (GET (CAR HoLnl =TOK) (CAR WOLD) )*(Gc PP) 1 )

(Ct')NC ((PF?€FMATCH(CPR H?LD) (LIST (GFTR SUB,) )T )

'( (f (PREFMPTCH (CAR HOLD) GLST) 7) KJ~)) P2 (SETQ HOLn(CDfi HbtD) l (Gr) A ) 1 ) ) P I (P ~R (LPMBD~ ~E (SNTC) (PRCG (++ NnSEF Hp HnLD GLS? LFV) +PARSE CPLLS ATN BY SETTING LEV-EL TO ZERO Ah0 'PUSHING TO CLAUSE+

(cLEARRFGs REGLIST)

R SET^ LFV * 0) (9E7Q (CAR SNTC))

WRWTIpySH EClrPUSF!)

~c(?ND((~ET- * :DET) .~SET~ FOG Q) (sETQ VB I IS ) )

((SEW FOC(GFT 4 =qUPJ) 1 (SFTQ vw a ) )

((SET0 F,OC(GET @ =OPJ)) (sETQ VR * ) ) 1

~ F T L R (CPR ~ rw~ I ) (SHQM~LAMB~A (TCKS (cO~D ( (NULL TOWS) f Drlhlp) ((PR INT(CA~ fob€$)) (PRJ~T(PPR~)P(CAR TOKSN )

~ ~ HO N ccna rons)) z l +FINDS ~TECEOE )~~TS FOR. PU~NOUNS BY CHFCKING PERSON AND NUMBER,,.CLQ~NS ARE EXL LESS 4 (fiNTEC(LfiM0DI(PRON CST) (PRoO(CANU)

(CON0 ( (NULL LST) (RETU9hl N1 L) 1

(sETQ CANE (CAR 'tsf)

ICOND ( ( A ~ (€0 D (GET PRON SPERS) t GET C~ND ZPERS)

(MEMRER (BET CAhO ZNRQ) (GET PROV ~NRR) 1

(RETURN(CPR (GET CANQ gull) ) ) 1

(T (WTbF?IU (ANTEC PRON ('CnR LST) ) 1 ) 1 +L&X~CON AND LEXl FORP P PROPFRTY THE FORM SHOWN Ih (LFXICqY ( , ) 1 (LEXICON (LAPPD~~ (L)

[MAP L (FG1107F (CAhdeaA (\-I (PQ ~ ~ z

(PUT (CA~R L-1 (CADAR L) (CAAH L) (LEX~~CAAR L) (CDCAR 'I-)) 1 ) ) LIST STRUCTURF FROP ) , ) ) I c THIS FILE Is A SET OF LISP FUNCTIONS TO SIMULATF SOHE 0 THE PRIMITJVE FUNcTIOhlS OF THE M . IaT . LOGO LANGUAGE AND I~TERFPCE ~b THE GFSYS SOFTWARL FOQ THE Iwnc ISP PLAY TERMINAL. ~~RTTTEY i3Y GMCON NOVAN mj.2.9 YAY 74* J( GLOB~L I~ITTA ,LIZPTIQ~ . FNTER (I,CGO) SYSTEM AN^ RETURN 0 TQ HAINCnOP c (LOGO (L~MBCIL (PRO6 lTPFy THETA STHEJA CTCFTA

GLOBALS J.ZE SSCALE C~CALE X ~ a kL f YTOTAL

THE~A~ SCREENXPAX ~~REENYMBX CSXZE P$IZE- ITEMAD

~XTOTAL TYTOTAL PIIRO

UNlVOO P ICSCC *TRA~E * MAS~$CL 4 TO START TME

1 (LTNTT) (MAXWLOQP) 1 ) ) 4 IN~TJALZ~ATXQN~ ENTER (LINIT) TO RE~ IN IT IAL~?E AND START A NEW PI[CTURE, 0 .L (L IN lT (LAMBDA (PROG o

(SET0 OL70RhLST2E 13)

(CSETQ P11~t) (QUOTIEAT 3,34159265,3SR98 1.80c0))

(SE~Q CSTZF lad)

($E*TQ (s€Ta PS1ZE '"h JL) SCREENXMAX 1023.0)

t?aETa SCREENYMAA 1023.0)

rtER€Ao)

(PENUP)

[WEADIRG Ct,W (RET l~Rk) 1 1- 1 4 NEWFRAME -SE&DS COMMAhDS TO THE TPLAC TO ERASE THE SCREEN ANn PEcREATF~ THE F-RPME =LOGO. JI (NEWFRAME., (LAMBDA ( (PRIIC; 1 W"wT EER NXL) CSETQ ITADDER 2048) J1 E IS A SHQRT k (E (LAMBDA 4 ERASE THE SCREEN A W ALL-TMENS ~ IN UNIVERSE CF'OISCOIJRSE s (ERASE (L'AYBDA (1 (PROC~JATP~ A (~c0Nr-j (: (NULL IlhIVQT!) (60 P) 1 ) SET^ h y ~ (CAR UNIVODII

(PUT 'ATM -~~MLAC ITEP h LI,)

(DELTTEM AT*)

[GO A ) R (NEWFRAME)

( RYTIJRhc

OF ERME TO ERASE YE sCAE~N. (ERASE) 1 ) J, ) ) I + LIST PROPERTY L IST RELPTTovS flF AN A7W r EXCEPT PNAMF~ T-NFO, 4WD EXPR. JC (t1$TRfL (~4L49b4 (ATW (PRQC; (X Y )

(PR~NT ~LA~K )

(PRtWY

(SETQ X A (CONO (SETB (CONt) tPRINl (PRIw1 (PRIhdf R (en A ) $I TURN TURTLE HEPDING Td THE RIGHT. A ( R ~G H (LAMBDA ~ (N) (H64DTNG (PLUS N THETA)))) J, TURN TURTLE HEADING TO TwF LEFT, 4 (LFFT *(LAMBDA (N) OtEPC I~ IG (DIFFERENCE THETA N) ) 1 ) Jc GSTARLTSH TURTLE HEADI~G-, AROUYENT TS HEAO I~G 1h AfM)

(CSR BTM ) ) ((NULL XI (RE~LR~ ) ) y (CSR ((OR (EQ Y EPNPMF) (EQ Y :INFO) (EQ Y %XPf?))

(GO R ) ) )

BL~NK ) (PRIhl A (PR-EN1 Y ) (PRIhl COLON)'

BLANK)

(CAR X ) )

(CDR X I ) OEBREES CCOC((IWI$F FROM 4NQRTM~ + (nFaorNo ~LAMRDA (TH) (PR~G (I

(CONU* '(pa (oREATERP TH 360Qr01 (LFssP TH -36h0 00) )

~E~ROR . (ARG OF HEA~~NC 100 RIO) ) ) 1 b B ~$ETQ-THEPA TH1 (CONI) t (QREA,TERP THEM -0.00060001~ (Go 0) 1 ) (SETQ THE74 -(PLUS THETa 760.0i) (GO' A) (COND ((LEssP TWfP 360.0) (Gn C ) ) ) (srTn WETh (DIFFERE~GE THETA 360.0) ~SETD $THETA. (SIN THETWI [SET0 CTHETA (C0S THFTh71) csda SCALE (-TIMES STHE.TA' c'S!ZE) tstrn CSCALE (TIMES CTHFTA CSTZE~) ( RETUR~ '~ + PICK THE luR~ ,b ,~r 0 ,S PEb UP, J, IPFNIJP (LAYRoA (SETG TPFN NIL) ) + PUT THC TURTLE~S PEN B-Owy a J, (PENDOWN (LPMROA t (SET6 TPEN T I ) ) C MOVE WE TURTLE BACKNARD$ rRnCN (LAMBDA (W ) (PORN ~MTVL& w ) 11 ) Jt MOVE THE TURTLE BY A SfGh~En.A~OlJhT 4 VWVE (LAMRDA (W ) WORM w) 1 ) JI GENERATE OUTPUT COMM4NCS Tq THE IMLAC Q IvE~ THE COMMbND wa~b a ~ o A LIST OF AIGLMFNTS. 4 rmu7 ~LPMBOA (COMMAND PC~,ST) (PGOG I 1

(PR f ~l DARPQ~ 1

c ~ R 1 ~ Cnv~ahol 1 A rcaNn ~-(NUL'L PLXSTA (TERPR~ 1 (RETURN) \

IPRINI BLA~K) '

(PRXNI ICdR FLTSf ) I

(SET0 PL I~T (C09 PLIST))

[GO A) V l JI C FORW WVES ~ i H F TURTLE BY A SIGNED PYOURT IN THE CURRFNT 0IpECTLOhv IF TFE p€h Ic TIOWN (IPEN = eE DRAWN. (FQRW (LAMBDA (W ) (PPOG [x Y TX 1Y XP

rsETp X (TIMES CSCPLE w ) )

I%E~U Y ITPE5 SSCPLE kr ) )

(SET0 XP (PC%S X.TQTfit Y ) )

(SET$ YP (PLLS YTOTAL Y )J

(CON! {(OR tLFfSP XP 0). (LESSP YP n l

(~G~EA~ERP ;P ,SCREENYMAX) )

$-GREEN)) (RETURN)))

~ S E ~Q 1% ( IROYhO ~DIFFERENCF XP IXTQTALI ) 1 (%TO IY (IRCURD (DIFFFRENCF YP 1'I~nf AL) 1 1 ~SE~TP ~XTOTAL (PLUS I% XXT~TP~ ) ) (~ETQ SYToTaL (PLUS Iv rYT0tAt) 1 I$.ETQ ~ TO T ~ XP) L ~E TO Y ~O T ~ YPI L ~CQND (PPE~ (GOUT ZLI (LIST IX 1~ ) ) )

(1 (GOUT EM0 (LIqT 1% 1~ ) ) ) )

11) TI r A VECTOR WILL YP) (oREATERP XP SCREENY~AX) (ERROR 5 (WOVE WOuLn no OFF TRfiUND ROUNOS A hUMRER TO THE CLCSEST TNfEGEP- 4 ( TROUN~ rL-hpPv~a (XI

(CQND ((MINUSPI X I !FIX (l7lFFERENCE )r 0.5) 1 )

(1 (FIX (PLclS % n,W) 1 1 ) 4 PO$I?I%N SFTS THE CYRRENT POSITTON OF THE TURTLF TO A SPEClrTED VECTCR POSIT TO^, SUBJECT OYLY TO TttE SIZE FACTOR GLoRBLsTZF. A VECTOR IS A LIST OF THE (X Y ) COOROTNATES* 4 (Po~ITIuN (LAMBDA (V ) (PQflfi ( tX IY )

(sETQ

(SETO

tCOND (SETfl (SETQ (SET6 (SETQ toout C SCALE SETS A LCCDL SCALE (TN bOnlT10N TO-G~OBALSIZE)~ AND MAY BEm USED SFY THE SIZE OF SOMET~JNG To RE DRAWN ~ '~THOUT MULTIPLYIN@ FVFRYTH I~G C)ljT, 0 c (SCALE mwWm~ ($1 (PRcG

(SFTO CSIZF '(TIMES S ~ I ~MA L 1 ~X ~E ~ .

(SE~O SSCACE ( f IMFS. STHET~ CSJZC)')

(SFTO CSCALF (TIMES CTvFTA CSTZF)) 1 ) ) C PUsHSC4LE PUSHES OQWh THE cURRE~IT sCALF AND SET$ THE CURRFbJT SCALE FACTOR TC THE SPECIFIED VnLUE. HE COCPLFCENTARY ROUTINE POPSCALE JILL RESTOPE THE SCNF 70 TkE PAE~IOUS VALUF rlr (PUSHSC~LE (LAWBDA (S) (~RQG 0 (SETQ PSIZF (CONS ~ $ 1 2 PSI~E)) ~ (ecdLE S) ) I ) C POPSCA1.5: WILL RESTORE TH'F +CAI-€ FACTOR TO THE PQEVIOUS VALUE ~AVED av PUSHSCALE. '0 4 P POP SCALE (LbM@Db (PRfi6 ( 1

(CONr) ($~rf3 ( (NbLL PSIIE) ($CALF 1 1 (RETURN) ) CSXZF (CAR PSIZF) )

tsE.Ta SSCALF (71~cf STrCTb

SET^ CSC~LE (TIMES CTuFTA

(SFTO~'PSIZF (Cod PPSIZEl) CS~ZE ) CS lZE)) ) ) C A VECTORI FOR FURPOSES OF THE FDLLOWINC vECTCR ROUTINE^^ IS a LfST OF: ? ' VAtUESr TUE x ah0 Y COORD~N~TE~ ;~ VSUM FORMS THE SUM O f TWO YECTOPS AS A& ONPUT vEcTan. rvruu (LaMeCa rv l VZ) (LyqT (PLUS (CAR V ~ I (CAR ~21)

(PCI~C (CAOR V1 ) (cAOR-VZ)) 1 11 4 G VDIFF FORMS THE O'LFFCR€N~F:~~,F Twc,VECrnRs 9 [VnI.FF (LAMBDA (V1 V2 ) (lal$'T ~D~FFERENCE (C4A V I ) (CAR V2 ) 1

~~XFFERF~CF (CanR V i ) (CAnR v2) I ) ) ) e VSCALE SCALEyb VECTCR RV A SCAl-bf?, JI (35~4L~ (LAWRDA (V S) (LfqT (TIMES (CAB V ) S)

(TTPFS (C4DR \I) s)) 1 ) TX i~ (TrtQF:S (CAR V1 RLORAI.SIZE! j (TIYES (CPDP v j QLOBALS~ZE)) ((OR (LESSP IX 01 (LESSP TY 0) (skEAT€f?p Ix sCREEN~QAX)

[GREATERP TY ~CREE~ IYMAX) )

(ERROR i(PqSfT1Oh I$ nFF

SCREEM) (QFTURN))) X f f lTb~ 1x1 YTOTRL IY? IXTOTAL (IROUND 7x1 ) IYTOTAL (IROLhD TY ) ) ZMT (LIFT fx707ui YYT~TAL ) 1 ) ) {VRQ? (LAMBDA (V TH) t?F?flG_(STH CTH) (CoND ~(LE$sP< {AHS TP) ~ .OQ~O~ ]* (RETUPN V ) ) ) ISETQ S ~ H (SIN '(JfPEs TH Pr18mr

~ S F ~Q brq lcos ~TTHES TH ?I1861 1 )

(RETURk .~CTS~ (DIFFERENCF. (f IVES (CAR V) EfH) (TIMES (CADR w)' STH) )

(PLUS (TxWES (CAR V) S.TH). [ ~ I M E (CA~H ~ V ) ~T t i l ) , , ) ) I .I. pECt DRAYS A RECTANGLE Fanr THE CURRENT Pn$fTIONp T-HF ~RGUMENT~ A~E : THEd NU&RFR AND THE ~VMBER OF UNI'TS sn THE a Ie~ f 10 THE ~?E~~@NGLF . CRECT ILAM~DA fFW *RT? (PRO(; ('1 4FCsRU FW) (RlGPT SO) tF0sw RT) (RIGHT 901 (FCRW FW)

RIGHT 90) (FORM AT) (RIGHT 907 1 1 1 Qb PoS P051TIOhsh THE TURTLE RFCATlVE TO ITS PRESENT POSTTI[ON WTTHC~T DRAWING P LIhc.. TME ARGUMENTS ARE THE NUMBER OF UNITS TO MOVE FOCidARO PNq THE* NLJPRER OF uN~TS TO MOVF TO THp RIGNT, THE ORXENTAT I~~ I3 LEFT 65 REFQDE THE CALL. + iP0S (LAWBOA (FW. AT) (CRO'G (SDE'~J)

cs~la SPEN PEW (FEhUp)

(SE~Q ANF (VING (LIST FN RT !h

~PIGHT ANGI

trow ~ V M B (LIST ~ FW RT ) ) )

[LEFT 4Nbl

ISETQ~PEN $PEN) 1 ) ) oRIE~TPTION- AND hF UhJTf FORWARD BE McvEn IN M'AKING .Lr VECT 'ORA~S CI VECTOR NHICbl- WILL GO FROM THE ,CC'f?RFhT Pr)SITTOP' awh OR IENT~TJO~ BY A SPEC.~FIE~ AVOUNT fqRWARC &NO A SPECIFTFO AM~UST TO TPE RLG~T . THTS IS NFEOED RECAUSF IF IS U'SUPLLY TH~cAsE THAT EITHER TPE LFNGTH CR THE ANGLE IS b Nb5TY NUMBER, 4 tvEC7 (CAMBOA (FW RT) (PRO6 4bN61

(SETO AN6 (VANG (LIST FW RT) ) I

~R~GHT ANG)

(FORM, (WMAG (LIST FW a7t) 1

(LEFT 4~31 ) I ) & PTSPLAY CLOSFS THE cL'RF~RT ITEM PNO AnnS I t 70 THE CIJRFIENT FRAME SO IT WILL BE DISPCAYEO, I + cnrSPLnYA ILbMflCa WRdq 1, 4 SEN0 4 COMMAND ?'n THE LAC TC CLOSE THE C~JRPEMT ITEM* c teou? Ecc MIL) ( RETuR?~ 11) + DELI~LM DELETES AN TfEv ROTH FRfW THE LISP DdTA STRUCTURE AM 7 FROM THE ors~trv . + (DELITEM (LP~ROA (TOklrrbM~) (PRDq ( (GONO c (GET TdKNlrE fIvLoc1TEW

tPA1~1 EDI) (PRINI BLA~K): - (~R?h j E+JIJIV) (SPIN1 TOKNAME) r TERPRIJ 1 1 (DELREL (OFT 'FOHNAPE ZTQKJ ZTfiKENS TOKN4ME) (SETO UNf VOD (REMLIST T~KLIAHE UNIVOD) ) REM MOB TQKNAVEJ ( REf URk) 1 ) ) C DELREL MMOVES AA ENTRY IJN~ER d PROPERTY LIST ~NOICA~QR VHI)SE -LEFTMO?T ATOM 15 b5 ZPECIFIEO. c (DELREk (LbMflDA (ATOP REL VALUE) (PRO6 (PROPS I

tdo~n t (NULL, (sera PROP$ (GFT ATOM RFL) ) 1 (RETURN) 1 )

CPb(7 ATON REL (REMLIST VALUE PROPS))

(RFTllRN I 4

REMOVE A SPECIFIEO fT.EP FQ ~M THF TOP LFVFL OF A L IST + EMLIST tLAMBUA'(VAL b\$T) (PRQG ~TMP ] .(CON0 ( (NU-LL LST) (PFTURh') 1

( ((EQ (CAR LST) VAL) (RETL'Rhl (COQ I- ST) 1 1 )

(SETQ TMP I LST (~cND (NULL (CDR CSF) 1 (f?ETL;Rh TuP) l

((EQ l (CPr>R LST) VAL1 (RPLAc~) LS\t (CDOR 1,571) pEf \lRW TV,P 1 1

CSETQ LST (CDR CST) )

(,GC A ) ) ) I $. CARATOM KEEP^ T IR ING TNE CAR nF THE ThlPUT ONTTL IT FTND$ bh ATOM 4 (CAQAT~@(LAPROA (X ) (Cbhn ((ATOF X ) 10

(T D( '?4~~~nu (CAR x ) ) I ) ) ) + A'BsUAL RETUR~ I~ TNE AeSCClr7F PQSTTIOM OF, A POINT IN QFLATlvT COORDINATES Oh1 Ah OBdECT WTCH HAS BEF~I - POSttfOhlEb RY QRTE~TI 4 VVlSVAL (LAk9OA (OBJECT WCP7) (PROG (MODEL bnEl APT)

SET^ WOOFL (GET ORJECT ZTOK) )

(SET 0 UDEL (VSCALE (VOTPF RELPT (GFT MODEL STARTP PI) )

(I'JE,T O'BJECT sS17E1 1

(CCND ( ~SETO RCT (GET ~RJECT 5 ~ ~ i 10~ E I ~ ) ~ d ~

(SET0 VDEL NPOT WDEt RCT)) , ) I

(RETuR~ (VZUb' (GET ORJstT ~STVPL ) VDEL) 4, PUTRELS PUTS 4 (ib?LNC. CF ~w lNc;S CN AV AToW+S ~F?nPFflty ~ 1 5 ~ ~ THE ARR~~HEIJT 15 4 LtlST OF THE ATOM, FOLLOWED RY IN~ IcATDD ~ND VALUE PPTRS, + (PwTAELS, (L~,PPOA 1 (PRnr, (ATOM REL VILUE)

csVa ATOW (CAR L1) A (CON0 MI, ((NULL (SETQ L (SETQ ICP~R L)

tcowg ((NULL (SETQ L

(SET0 VALUF (CAR 1-1)

(PUT ATOM PFL VALUE)

(OC A ) 1 ) ) J. A~JSOLIJTE .VALIJE (48'5 ( 1A~~DA ( 1 CCQ'hD ) ) ) d ) &DISKOUT IS TME FUNCTICN RY M~RAY THAT GIVES VIRTUAL MEMORY F ~ R FbhCTrncS. (SDR L) 1 I (.RETURN) 1 ) (cna t111 (F?E7~?lu))) 4 .( ~PTNUSP X ) (YTNUS XI) (T X ) 1 ) ) TYSnh Uq C t **z LF F>d] W*

OX xmc U a Q L' a =W Z L L ~ o ruse ct-> c3z LW * OIT3 *J o d tW uom L L ' ~ *LC a3- aw 2 I 3- W czc w W O ~ ak v;.** X OW J * uat k w- CnS - wo rr A= - r-

W +A +U W u4 1- 3 3 W - X >- u am C - I Cz--C-ZO - -a d a! c~~n a a w5) w ~ JW Jc~h D J Z J P. --a-LiO: w e a aOC > -Zd - k WOW S+Cr:--U z I++& ~a Z3k YX d - >+ C JW A WF a CL r JCEQ>' >a W- n e-P FLL O X 3X - Ld-0a-a e .A W F iQ C34tdZOb- F F UCL wze-v, 0 -5 --dJAI PA -q- WFC34 .a X4WQJIrUJKK- &- l~J0~3~0-3U 04 3-a 214 D * r a YW---Y:eoc.V tXQQ J' f -- WZu oe r;l tLw- - -K +X tUw > a + J Y Ln X - k d - 4. m 111 Y t+ o ww rrwn Irb-- LL r 000 a Q - 1 1 1 0 0 Ol-0 tY : @

CC em C -- + - aa- O+ aa 34 2 wa f11 III xe t C R k wu-lx, UYwc?i. Cha- x- en- - k 3kFCf~- ~ a ~w ~ + : r ; 3 - a CWZWC3 G,uuVIQQ P I-PIII -k4 m a V c V)V) , W - JJb-kH -WYF&-Z 0- A UI a n1 -- a - LD o ~-u>e+w i-++ Y a ab -- COC OOW~~WLJU 4 : I~~ -r Y OL o 3 FL W r u w 'Z l- u L td V) W I F 0 r (r lL u 0 z w e a w P: k 2 +Q DOUOkiwQ YW L ILYJ2WUW uYV 7 - L Q:+L+CCZ Q tA o &.! 2 J 4 > V) a N 0 P 0 u t W n CI N a IT a CL IV) Y

O W a 0 C t V 3 C Y * V) Y Y 0 o a a - -he* 33 w-,*- X-X UI ++m QWVI O--F-t- WVI W WQQU -uW LC + C C% P* -kQ k I ( IkO + I cnn; t DOC-- a was llf a 3q 4 + YWCT rtr I~I +I- J - map V, L a wwbca3uo xe wa aao ;up 9 cr ooa nW -13 kW W (30 >W gU LEO:& ~ tr f~ ta+ id - - - -c - ao. Ln-C-+P AA+CC~C~OA 141 W + x 3 h: U 1 JYZ q ~ h w b UJ w a, dm-b-e- - V *PI uzeck-z I- adon c z kc fL 3 Q)CO?C- O+C~WQ 22k aw auzzwb -tn - vrsraa a-- Y Xk*O a Q~- JZ 2 Q c do ~ U j u WfLM O~L --tL --a0 QW -+ o a ff a 0 k tf 3 A > W t+ I L w c t uz (3W Y a C 04 w r +- in w w+ 0 tn w@- ULT z otm 33 0 ZO OW or 5c 05 ~ UP o t

CC LL C + c LLF ~na-a axk vr r w e 3CrwIm +v, a Z I aa -ZOL It UDH rn u OW ~ k V IOW ~ Z V~UU k tUW -- 3rna.n~ *O dr A ww , wdzm ow 4 *ZW , L12 cn' 3 W e JWO nvmkx+ WJWm iYQ3:B-a Ul-lnmktd a c A Y-w wa: m Q vlF4b-xa kOZX tl EJZL zw E. ~ 2 - z c I.S id= 1 kkd w W* t C~b.eIrc~aC,fr rmm tp ua F ~(3I0'3 F~;)~~~(L%U 7 XL+QU+W a -0~~ IY -w* oc r a ~ ow a O a x Ut-Q m r a WLT rxw i *-mwa r o C J - ~ Z U V ~W Z aw ~ r33 a w# e e W t- ee *QV ULOH UA W0-k t-t A* 3, am* .am 'WW U? P-WAZ 0 % T-& tea. q=' WH UZwr4V1WW ~Q E~Z : m a )cas~cpwam 3 3 %5 ~4-0 -MeP.W W+XPZ warn zamav~ o w4 ew - > a W23~jaUW- jE: . .rama+t am 3-J wo OX LWeQX.L36PQ: ~woar ' fw wzw + =Pk+0b&+00443 +ZCP WITH LEF'TOP ANC RIGHTOF TO PRODIJCE A PTCTURE W I TH BOTH RELATIONS SATXSFIEDr NOTE'THAT THIs 'VERSION DOE5 NOT USE THE PROQPPM -DIAGRAM-, 4 (COMPIcS (L.CLPESCA 0 (PnOfl (AFRAME BIFFRAME TKS TK PFA PFB

ETWAS" TK8 TKC AtTP ATTPOR YA YB TMP) 9 MAKE A PF FOR 'EACH TnKEN AkO PUT ON THE PROPERTY L IST

UNDER T H ~ ~ANF PF JI

(MAP TOKS (FGUQTE (4PMqnA

(PUT [CAR' X ) ~ P F (MAKEPF (CAR X I ) ) ) ) I

GO THRQpOH,AND SEE WHAT WF CAN c~MBINE.

(SET0 T&S ~OKS )

(SETQ O~FFP~W MU- 'E NIL) ($€f'g EfWAs

(s~TQ PFRAME, (GET (CAR TdKS) ZPF) )

(SET0 fK (CAR TKS))

[SETQ, PFA (GET TK EPF) ) (cAND ( (NOT, (EQ P f b P~RAME ) ) i) (SETQ OTFFRAME TI ) ) TEST FOR U~~AT ISF IE~ RELATIONS ) . JI tcnwn ( (~J~S .ATR TK '?LEFTOF) Go )

((ldNSATR TK ZR19~Tr)f) (GO R ) )

( [IlNsATf? TK.4SL'PpnRT) (60 S) 1

( Luk~n t~ 1~~ ZBEL~W ) ma k) 13 END OF TeE #INNER LPOP 41 (COND ((SET0 TKS (CDR TK5)) (GO 9))

( (NULL nIF,FRAF(E) (nRAwPyCS (GFT {CAR TOKS) EPF) )

( RETURh) ) (ETWAS lea F-~ILE:~)) AM ) (PRINT E(CVMPYCS (RETtlRh ,

IlNSAT'IsFIED LEFTOF- PF'LATLO~ JI ~SETO TKO (GET TK ~L ,~FT~F ) ) (sET~J PF9 (GET TKB EPF)) (cflNo (ANY \~~SBT K& ' =(PTGHTQF)) (131) K) 1 ) tCCAl,E5CE (LIST. "(CADAR PF4) (C~SQAFI PF!) )

(LIST (CbAR BFR) ~CACDAR RFR) 1 ) & A C R ~r JI K 4 L J, R (GO K)

L~NSA'TISFXEB RIGHTOF QEL~TT~N + (SE~TS TKP '(6'E.T TK ZRfGwTqF)) (SETQ PFR (GET T68 - =PF) , ) . (COND (!AhyUh$bT TKB Z(LFFTOF)) (GO K))) ~COALESC~ (LIST ( 'CIPR PFA) ~CAODAR PFA)

(L IST (CAOAR PFB) (CPDDAQ PF~! 1 ) c s J( W (GO K )

UNSATISFIED SUPPORT PELATTOM JI (SFTO TKp -(OFT IK ESUPr=lr)QT) r (sET~J PFB (GET TKB 'ZPF) ) ICQI'ID (SUB t ( AhyUhSAT TKB 5 (sIJPPORT~Y 1 1 (GO K ) 1 TMP (CAR (GET 7: =ATTACH-) 1 ) ts~ r r~ PTTP (EXECIOC t ~ n P TMP) I (sETo AfTPo8 (EXECLOC ~CADR TMF))) (Cobln t (EQ (CAAR TPP) TKQ) (SFTQ TMP AT-TP)

($ETG ATTP ATTP~B) (SFT Q ATTPOR TMP) 1 ) ~CCACESCF 67f P ATTPOQ) (60 K)

uNS~TISFJEO BFLOM WFLATTON JI (SF~Q TKR (GET TK 50ELqw)) (SET0 PFR (GET ~ K R 3PF)) (SETO '?A ((PLUS (CADR (GET TK ZSTVAL))

(UIFFERFWCF (CAQDOR (GET TK IORIGPF) 1 (CPOQ (GET TU ~OQIGST) ) 1) (SFTQ YH (P I -L~ CCACR (~c TKR f ~sTVAL ) 4

(DIFFERENCE (CADOR (BET TK8 SOR IQ~F~)

(CAI"$!' (GET TKB ~C IRTGS~ ) 1 ) ) ) (CON0 ((ANYULSAT TKB kt4RQVE)) (00 U)))

$IMPCE RELOW* hO LFFT OR RIGHT, CENTER PFSI 4 (COALESCE (LIST CTIMES (PLUS {CAAR ?FA) (CAQ4Rm PFA) ) 0,51

Yf i) (LfST (trMES (PLUS (cAAR PFB) (CADAF? PFR) 1 0.5) ~ 0 1 ) (GQ #)

BELOW WITH LEFT OR R IWT + ~coNo.'((ANYIJNSA~ THB ~(ARQVB I-EFTOV RIGHTOF)) (GO 101

( (Ubi~bf R TKB ELEFT9F 1 (GC V ) 1 ) RELOW'WITH RJGHTO~ 4 rsrTa TKc ~ ~ ~CT - ~BZBT OHTOFTI [CONll ((NOT (MEMBER TKc (cDR PFA))) (LIST (GO K ) ) ) (COALESCE (LIST (CAAP PF4) YA) (CADAR PFB) YB))

(60 *K) 4 BECQw WITH LEFTOF IL V ~SETQ TKC (GET TKB SLEFT~F))

(CON0 ((NOT (MEMBER TKc. fCDR PFA))) (GO K ) 1 )

(CDA~,J~SCE (C'IST (CPOAR PFA) YA) (LIST (CA*d beel YR) 1 )'I) ~OC) K) + TEQT FOR UNSATISFIED RELptTdN 4 (UNSATR (LAFBDA (TOK REC)

(AND (GET 'TO& REL) (hbT OAEME~FR (OFT TOK (CDR (GET TOK ZPF)) 1 ) ) 1 ) RE\_) c U 4 4 TEST FOR ANY UhSATISFIEp RELATIO~ EXCEPT FOR THE GIVEN L IST t AMYuNsAT (LAMBDA (.TON I T (PROG (FL.0)

(MbP :(LEFTOF RIGHTOF AR~VE BFLQW SUPPORT SUPPORTRY)

(FQUOTE (LAYBOA o()

ccO~g (-tnhD (hOT (MEMBER (CAR x j LST) I

(U~SATR TOK (C6R X I )J (SETG FLG T I) 1 ) 1 ) + (RETuR~ FLe) 9 CO~LESCE TWO FRAPES, PFA AN9 PFR, AT THE GIVEN POINT5 + (COALESCE (LAnBnb (PA PR) (PRoG (PF)

f SETq ETdAs 1)

t$E l~ PF (COFPFHM PFP PA PFQ PB)>

(MbP tCDR PF) (FQUGTE (LAMBDA (x)

(PUT (CAR X I SPF PF) 1 ) ) ) I C sUBROUTI~E OF COPPIC5 TO SEE IF THERE IS AN COJECT W7Tr THE d€&~Trohr REL AND SET PFB,-TO ITS PICTURE FRllME SET s (FNDcPc I~AMR~ ' CREk) )~ (PooG (PFT~ G $EE IF COB HAS SQMFTHING 1h THIs'RELATIoN J

(CON0 ((ROLL (SETQ O@ (OFT CQR REL))) (RETURN))) G SEE IF,OhE Of THE OTHER PF SETS HAS OB IN IT ~SE~Q PFT PFS) A (CON0 ( (NULL (SET0 PFI (CDR PFT) 1 ) (~ETUQN) )

( (WMRER. 00 (CDAn PFT) 1 (SFTO PFQ (CPP PFT) 1

(RETUHN I) 1

(7 (60 4 ) ) ) 4 ) 1 ) G TEST WHETHER PA PTOM OCCIJRS IN A STRUCTURE ~1 (OCCURS (LAw.~ae (ATM ~IL) STRI (CON0 ( (NULL 5TR)

(4EQ ATM' STR) T') ( (ATOM sTR) NILb) 64 (r (OF, (OCCURS ATM (CAR STR)) (OCCURS AT# (CQR STR)) 1 ) 1 ) ATTACHVENT RELAYT~N c

(LAMBDA (A PP R gP) (FROG (TMP ATTRS ATtR TMPB) TMP .('LIST (LIST A PP) (L IST R RP) 1 ) ( ~NUCI+' (sETQ ATTAs (GET P ATTACH)) (00 C ) ) ) A ~ TR tcnR ATTRS) ) ((NOT (Eb (CAR (nTHER A~TR A ) ) 0 ) ) (IGO F ) ) ) ((NOT (EQ (Cb IR PTTR) A j ) JSETO TMP~ AP)

(SEN PP RP) (gETQ RP TMPB)) ) ( (ANn PP (OR (hOT (EO 1cAR AP) ~DEFAULTLOC~ )

(MULL (CADAR &?TR) ) )

~PPLACA [COAR bTTR) A@) 1) UAkn ep (OR (hiof (€0 (FAR BPI IDEFAuLTLOC))

(NULL (CADADR ATTR) 1 ) )

(Rp~4C.4 (CDADR ATTR). RP) 1 ) ( (~ETQ ATTRS (cm ATTRS)) (GO o))) * MANE AN (MAKEATT

(sETQ

(COND D (SFTO

tCQND

(CONn (CON0 (CnNn E c QPEW AN ITEM Oh THE lpLAC + (OPEhlTEM (LAMBOP (TOKhAMEI (PRQG (1 (GOUT ZIT (LIST IT~DOER 260 n 328311) G U T (LIST I~ADC IE~ ) ) (SFT~J TT~OOER (PLUS ITAO~EQ 200) I

(PUT TOKNPME EIMLACXTEY T*)

(AFT \JRR 1 ) ) J, COMRTNF TWO PICTURE FRAMFs, a PICTURE FRAME IS -OF THE FOR^

((XMfN XM ~X VMIN YPAX I TOKEN TOKEN) ?Fa IS CQMRIPFC INTO P F ~ $n THC\T~ THE POINT P2 IN PF2 IS THE 'SbME AS P I ,IN PF1, 9 ~COMPFQM (LAwRCh IPF~ P I P F ~ PZ) (PRO6 ( ~ Ye 4 XP Yp cTPT

XHIN XMA ~ YMIN YHAX. TMP PF2P SP)

(sE~Q XG (CAR p.1)) (smn YA (CPDR P I))

~ Q E T XP ~ (CAE ~ 2 ) ) (SFTO YP (GADR ~21 )

(s~TQ X ~ TN (CAPG'PF-~)*) (SETQ XMAX (cASAR PFl-) )

SET^ YMXN (CAODAR PF1) ) (SFTO YMAX (CAODDA~~ PF1) )

(COW) ( W?FATERP (LEsSP SET^ TMP (NEwX (CAAR PF~ ) ) ) XMIFI) (sFT~ XrTb l THP) tco~o I (SETQ TMP (WkX (C~DAR PF~ I ) I X ~ A K )

(<ETQ XHAX TMo)))

(CnNf) ((LE$SP (SETQ TMP (NEWY (CADOAR ~ ~ 2 1 YWXN) ) )

(sFTQ YMIh TMP)))

(CONn ( (GREATERP (SEJQ TMB (NEMY

ttFfQ YwAx TMP ) ) )

LRPLACII PFI (LIST XMIN %MAX YMIN

(SETQ PF2P (CDR PF~ ) ] A (~€19 PC2 (cOR PF2) 1

(CO"+df3 ((MULL PF2) (REfllRhl (NFOhC

(SETO TMP (cPR PF2))

(S~ 'h l SP tqET TMP 2$TVa\-k)

~sETQ STPT (LIST (hEkX (CAR SF))

(PI!? TPP S ~ T ~A STPT) L

(GO 4 ) 11 ) + COCRDINATE TRA~SFORMATION FOR COMPFRM 4 (NFWX (LPMAO I ( X ) (PLUS YA (DTFFERENCE % XPI 1 ) (NFwY (LAMBDA Cv) (PCU$ YA (DTFFERENCE Y vp)))) ccoNn (s~TREL A ~A '~T IC \H IMP ) (sE~REL I3 EATTACH TMP) (RETuR~ (CADQDAR PF2) ) YM ~X ) YMAY ) ) PF1 PF2P)I)) (NFWY (CADR 1 ) a ) DRAW A PICTURE FRAM~ ,SET c (DQAMPTCS (LAMBDA (PF) (PROB ($72~ TFIP XMIN YMIN BAsFV

$TPt ORJECT ROT HODFL)

t NEWFRAME) JI COMPUTE PAX FROMG DJWENSIOL ANP SCALE TO THE CRT

(sETo ?3rZE {QIFCERENCE (CADAR PF] (CAAR PC)))

(SETQ, TMP t~lf~P;Rekcg jCPDDDAR PF 1 (cPQOAR PF) 1

t Co~o T('QRElJ,ERP 7MPL ST~FI (SFTO SITE IMP) ) 1

SAFETY' IN'CASE WE TRY Tn nAnW A ZERO 3tZE OBJECT

tC6Sf2 ( (ZFROP SXZF.1 (SFTB, STZF 180) 1 )

(sET;(J CLOQALSJZE (TIPEs 0.9

(flLON6Nfl SCR~FNXMAX SIZE) 1

FIX 19 HPAC~ '?~ TO KEEP FROY INCREASING PICTURE SIZE

~CON ~ ( ' (GREATERP GLOBALSIZE 5.0 1 (SFTO QLae~~sxzE s.01 I 1

(SETO 8MIN (QSFF.EREIYCF: (CP,AP PF)' (TIYES 0.05 SIZE)))

(sETQ YMIF (OIFFERELCE (CADDAR PF) (TIMES 0.05 SIZE) ) I

(SETQ BASEV (LIsT.XMIN YMIMI)

(SFTQ PF (20R PF) 1

(COND 4 (NULL 'PF) (RETURN) 1

~ S F OBJECT ~ I (CAR PF1)

(QP~ENITEM OBJECT I

(SFTQ STPT (VDZFF (OET OR JEcT ZSTVat.) BASEU)

~SCTO ROT (GET OBJECT ORIENTATION)) SET^ SIZE (6€7 'OB~ECT =cIZf?)) I ~PBS IT~QN QTPTI ccaNo (ROT (PEADING (MTNUS POT)) 1

t,T (HEADING 6 ;6) " 1 ) ORAM THF OBJECT J (SETQ -WOOEL (GET 00,JECT ~TQK I ) ((GET MODEL ZDRAWPROGI FTZE) (DISPLAY) (GQ n) 1 ) ) C PICK THE PART CF A PA IR WH~SE CAG IS NOT THE GIVEN ATOM. 4 (~THER (LAM~oA (PAIR VALVE)

(CUND ( (EQ CCABR P am VALUE) ~ A D R PA'XFZ))

tr (CAR PAIP19 1 1 4 CIEFIRE OVE~PCL PT,CTURE SCALE RY F INO IYG THE LFNlitH OF THE Q~GGEST bE1JEC'T FOR WHICH a .LENGTH Am IS SPECIFlEDr 4 (PICSCqLE (LAMBDA (UbO) tP900 (sCL S~LP-ICSCL) A (COND won cco s+ I

(CONO (SCC (.sETu PICSCL sCL) 1

(T WCSCL. 1*4)1,)

(CONO (MsCL . (SCT.IJ CPSS~~L MSCL 1 I

(T (SETQ MASSSCL 1 .Q) ) )

(RETUR~ C (SET0 tsE'fQ P7'M (CdR U801 1 UoD {CoR UobH

tcaNo c cnpo (SETQ SGLP (CAR (GET ATM ELENGTH) 1 )

taR (NULL. S P ~ C'AEATERP SCLP SCL) ) )

AN^ (SET0 SCC sCLP))) (S1E70 ECLP fcAR (GET ATN ZMASS) 1 )

(OR (NULL MSCC') (OREATERP SCLP MsCL) ) 1 (SET8 MSCL SCLP) ) ) 4 + + 4 + b 4 ccaNn 4 CD~JSTRUC~ A D I~G~AM FQR THE PHYSICS ~RQBLEM~ THE ARGUMENT IS THE OBJECT fD STAPT TWE DIfiORbM WJTH~ IL (OIA~RAM (LPMRC.~ (OBJ) WROO (OF~JL PJC~CL PF OR ORPF A B D C E

INPIC ATTRS ATTP ATTPnR ATTR TMP OBB) (SFTO OBJL (L IST 084)) (SETQ PF (LIST (LIST 0.Q 010 0.0 Q *O 2 ) ) tCQNf7 ((NULC.~BJL) (RFTIIRFI PF\)) cs&Ta QB ( c ~ R OBJL) 1 (sETO OBJL (CDR OBJL)) (SFTQ INPIC'(CONS ob INPIC)) ~SKTO QBPF. ({PAKERF 08) (SETIT (COW (CON0 (SETQ (GO R) ESETO 6SETn ('SETQ tCoNl3 (POMPFRM, LTTP OBPF ATTPOR) (SETC4 ~TTPs (GET 08 EATT4CH) 1 (COW ((EQ (CAP ATTRS) ATTR) (GO GI) ($€TO 7MP (CbR ATTRS) 1 (SFTO Of3R (ChR (OTFER,TMP OR ) ) ) (CONp ((MEMRER OBR IhFTCI

(PR'T.NT :(DRAWING

((NQT B E ORR

(SET0 QBJk (CCNq [COW ( (SETQ ATTRS (CDP (GO n) ~VERSPECIFIF~)) LGC 6)) ORJL)) OBB-ORJL)) ) ) .ATTRS)) ( 0 F ) ) ) G 1 ) ) C MAKE A PICT.URE FRAME FOR A SI~GI-E ORJECT 4 (M~KEPF (LAPRD~ (OBJ) (~sbr. (1 NG SPT 512 BASFV PF ~ Q MBDFI T 1

(COND ((NUI,L~SETQ S'lZ (~ET ORJ ESIZF))] (SETC SIZ 5.01))

(SFTO VOOEJ_ (GET -0BJ fTnK) ) (SETQ P f (GET MODEL EPpRAME))

(SETQ BASE\/ (VSCALE- (LJV (CAR PF) (CADOR PF)) $1~ ) )

(CO94n I (SETQ ROT *('GET OP ,~ EC~RIFNTATION)

~~ ,ETQ PF (RCTPF PP 'rlnT) ) 1

(sFT~ PF (MAFLIST PF (FQIJQTF ([AflHn~ (X I

(T IMES tCm % S52) ) ) )1

(PUT 083 5nRXGPF PF)

~SFTQ SPT (VgCbLE (GET ~ o b - ~ =STARTpT) - l SIZ) )

[CoNn (ROT, (sE~Q SF1 (V$UM (VROT (VRIFF SPT BASEV)

RCT) R A S ~ V ) ) ~ (PUT OR^ 5512~ SIZ) (Pl:T OBJ.Z5TVPL SPT) (PUT OBJ =0RfGST ?PT) (PFTUR~ Y PF OBJ)) ) 1 ) COMPUTE FRAME FnR A WQTATEn PICTURE 14 JAN75 4 4 THE ARRUVENTS ARE IX~ IN XMPX YMTN YMAX) AND THF ANGLF 4 (RoTPF (LAYBOA (PF THETA) tRRnG (DX QY STH CTW XS y$ )

(SET0 OX (0IFFERE.NCE (CA~R PF) (C49 PF) 1 )

(SETQ Oy (OIFFEWENCE (C~~QD-F) (c~DDR PF)])

( 5 ~ S ~ ~ 6 H (SIN (TIVES THFTA P T ~ ~ o ) ) )

(SETQ CTH c~.'f~f (CCS (TrPES THFTA Pji80) 1 ) (SETO XS (VRX 0 O ) (VQX cx 0) (VRX

(SFTO YS (LIST (VRY o Q) (VRY OX 0 ) (VRY

(RFTlIRh ((LIST- (PLUS (L~MYFJ XS) (CAQ PF)) ATTRs (BET 08 ( (NULL ATTRS)

(SETQ ATTPoB ((YEYBER (CAR

(GO C ) ) , ATTRs (CDR ATTRs)) =ATTACH) TSFT ATTP (LIST o 0) 1. (LTS ?t o 01) (GO C) 1 ) (OTHFH (-CAR ATTRS) 08) INPIC) ATTP (CAR MTRS ) ) RTTP (EXECLO!: (FAR ATTR) ) ATTPOR (EXECLOC (cADR AT?@) 1 ) ((EQ (CAAR ATTR) OF!) (sETQ TWP ATTP)

-(SETQ ATTP PTTP~R ) (sETC ATTPOB TMP).)) PF (PLW$ [LSHAX %S,l (CAR PF)) (PLUS (LSMIN YS) (CADBR PF) ]I (PLUS (LSMAX YS~ ' (CADOR PF) 1 I ) )'I) 4 MSN ANn MAX OVER LXSf S (C$MIfrl (LwE3DP (L)

(CONTI N U (CUB L)) (CbR L ) )

If (uIh (CAR L) (LSMIN (Con L)) ) 1 ) 1 ) (.Lsvax ~LAMPDA IC)

(CON!? (,(NULL (CDR L)) (CAR L)I IT '(MAX (CAR .L) JLSMAX (CDR L)) ) .I I ) + VECTOR ffQTATIOMS FOR X 'AND Y USE0 IN ROTPF 4 (VRX (LAMBDA ()I Y ) (CIFFERE~ICE (TIMES X ctn) (TTVES Y STH) ) I .I. (VRY (LAW~DA o( 'Y) &(PLUS (TIMES X STH) .(TIMES Y CTH)))) EXECUTE THE FU~CTXON T0 GET A LOCATION 4 (EXECLQC L A tL) (PRnG 0 (sE,TQ L ( ADR L))

(CONr) ( &on 4) ~~ETURN ( (CAR LI (COOR LI [CPDDR LI I.))

( 1 (RETURN ((CPR LI (CAOR L ) ) ) ) 1 1 ) ) 4 DEFAULT LBCATTCN, SAvE AS 6ETLQC IN EXECUTIO~ 4 (DFFAULTLBC (LAMBDA (L) (GETLOC L ) ) ) + GET P LOCATION IN OBJECT CDOR~INATES 4 (GETLOC (~APRW (L) - (PRQr: (ORJ~ MCML LflC

(SEW OBJ (CAR L))

(SETQ MODEL (GET43€% 3nro

(SETQ LOC tCPDR Lb)

(RETURN (PRSVAL OBJ Lor)l) 4 GET A RELATIVE LOCATfOh IN OBJECT COORDINATES J, (FROVLOC CLawc~ (L D) (PROW (QRJ MOOFL LOC TMP)

(SET0 OBJ (C4R L ) )

~SETO NOEL (GET QBJ ZTOK) 1 cs~Tn LOC (VSUv (GET MOOEL (CnDR I.) )

(VSCALE (SFTO TMP (UDIFF (GE-T PDDFL ZCGJ

(GET MODEL (CADR k) 1 ) 1 (RUOTIE~T (TIMEQ

(aUOT.XENT ~FLOPT (CAR 0) ) PTCSCLJ

(GET MODEL ~PsCALE))

(VNAG TM P ) ~ ~ ) )

(PiTkIRh (PflsVAL OBJ LOC)] )I , $. ERROR fabp RoUTX~E c rER@ kAM0OA ()WSG) (P~oG (RFX)

(PPINI ZEPROR:) (PRIhl MqG) tTERPS1)

~A~NLQOP ) ) 1 1 4 m ~ ERROR ~ f hcESSA@E Ah13 SURSTITU~E WQDS 0 FOR *S 4 (PRINTERR lLPM0OP (MSG 3) ARGS) (PRCG A ICOND ((EQ (CAR MSG) (PAINI (CAR AQGS))

(PAINI BLAhK) tSETO PRGS (CDR ARGs)) 1 fT (PRIql (CAR klriq)) (PRIN-1 LANK))) ( MSG {COR M S ~ ) ) (GO A ) ) (T (TFRPRI) ~RE 'TuR~J) 1 (COND