17 1024x768

run_$cneraL the top level goni. illuaratcs thc ncccssary initiali/ations for the cuunple «iscd m thc te\t: cłj<vtł nuy be 'nuli. medium or largo. their color may be red. blue or grccn. and *c* dupc nuy be bali. bńck oe cube.

run jjoneral

generał .to.specifictlL.JB-1 ].

llsmall. medium. largo], [red. Wue. green]. [bali. brick. cuboJJ).

29.    ImękmcM+tóemm+toiy for tbefloatc\amp!c inChapter9; mn it with prolog _ebg

30.    Eweni iw <k6amooebg **» that afer it coastructs a ocwruie.il ar^erts it to thc logie ditiKi-c .. herc * ■» he o«ed m futurę goeries. Icu thc performance ot thc rcsultiag tjv len urnę a thewy for a neb domam. You might do this by constructing a ihcm bf a domam .•! yow cfcoacc. or eucndsng tbe tbeor> from thc cup c\amptc to allow tto eiplaa diilacnt types of cups such as St>rofoam cup*, cups without handlcs. etc.

31.    Charter 15 prnatt a LISP implcmctiutton of the ID3 algorithm from Chaptcf 9. Usiag thi* implcmcnrjnon as a rcference. implement ID3 m PROLOG. Do not think of this m simply namlańng the LISP codę to PROLOG. The łanguages are di (Tereni and. likc diffa-cni natur.il łanguages. rcquirc ditTercnt idiom* to say thc sanie thing. Make your PROLOG fcllo* \\hat you fcrl ii a lucid and plcasing PROLOG style.

31 Build in PROLOG thc ATNparscrof Scction 13.2.4. Add who and whatqucsi»om

33.    Writc the PROLOG codę for a 'iibsct ofEnglish grammar rulc'. as in Scction 14.9. Add: l \d>vt:u*' and adsertn that can modify \cb> and noun*. rc*;v:tivcly.

h PrcpoMiiocul phrases. tCan you do thi» »«h a rccursis c cali> c Cmpwiiancutmo sentences jcćaeć by a conjurw non».

34.    The Mapie nalani languagc paner presented in this chapter will ncccpt graarabedb correct sentences that may not łu\c a commonscnsc mcaning. such as “thc man bites the dog” Thae sentences may be climinatcd from the grammar by augmcitfing the paner » inelude tomc notion ofnhat is sctnantically plausiblc. Design a smali “semantie nctwrfc” ui PROLOO (mc commenu in tcxt) to allow you to reason about somc aspcct of thc poisibłc interpretations of the English grammar rules, such as w hen it is nsuonabłe for “thc man to bite tbe dog."

35.    Rework the semantie net paner of Scction 13.3.2 to allow a richer rcprcscniation of cha hicnuchici. Spccificaliy. rewnte thc definitioń of malch_with_ inhoritanco so that instead of enumereting thc common specializations of iwo items. it computes this by scarching a typc hierarchy.

PART VI / LANOUAOES FOR Al PROBLEM SOLVMG

AN 1NTRODUCTION TO LISP

"The name of the song is called HaJJocks Eyes.' ~

■Ok thats the name of the song, Is it? "Alice said. trying to JM intmaed.

■\a you don 't understand." the Knightsaid. looldnga link \exed “That swhat the name is called. The name really Is 'TheAgedAged Man.'"

Tken I ought to have said 'That S w/uu the song is called'? ' Alice cometeJ henelf *.Vft you oughm t: that s quite another thing! The song is called Tbp ani Meansbut thaTs only wltat it’s called you kitowi ”

"Kell, what Is the song, llten? " said Alice, who was by this time completely bcwildered 7 mbs coming to that.” the Knight sald.

—U*t$ CARROLL. Through thc iMoking Glon

Stesimpllcity In the complicated. -LaoTżu

15.0 Introduction for thc 40-plus years of its cxistcncc, LISP Has bcen an imporuat languagc for afttócał BtcJIigcncc programming. Originally dcsigncd for symbolic computing. USP las bcen cuendcd and rcfincd ovcr its lifetimc in dircct rcsponse to ifae accds of Al appbcaboca. USP is an imperallw languagc: LISP programs dcscribe how to pcrfonn m algonthm. Thił contrasts wiłłt declarotiw languagcs such as PROLOG, whose programs aic awtf-tions that dcfinc relationships and coostraints in a problem domain. ł lowevcr. unlikc tradi-Honal impcraiivc languagcs. such as FORTRAN or Of. LISP i&fiutciional: its and Kaantics arc dcrivrd from the mathematical theory of rccunńc functions. The power of