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414451: ARTIFICIAL INTELLIGENCE (ELECTIVE-II)

Teaching Scheme : Examination Scheme :

Lectures : 4 Hrs/Week Theory : 100 Marks

Practical : Hrs/Week Term Work : !0 marks"ral : !0 marks

I. Artificial Intelligence Concet!

#ntro$uction to %#& characteristics o' #ntelligence& %# Techni(ues& )lock *iagram&

+riteria 'or Success&

State S,ace Search& Pro$uction System& Pro-lem +haracteristics.

Heuristic search techni(ues enerate%n$Test& Hill +lim-ing& cnstraint satis'action 2

ame Playing

Minmax Search ,roce$ure& %l,ha -eta +uto''s& Waiting 'or (uiescence.

II. "no#le$ge rere!entation.

%,,roaches 2 #ssues in 3nole$ge 5e,resentation

Pre,ositional Logic& #n'erence rules in ,re,ositional logic & 3nole$ge re,resentation in

,re$icate logic &resolution& natural $e$uction

6u77y Logic& Semantic nets& 'rames& scri,ts 2 conce,tual $e,en$ency& TMS

III %ercetion

*e'inition 2 ty,es o' Perce,tion& 8ision& S,eech 5ecognition&

9n$erstan$ing What is un$erstan$ing 9n$erstan$ing as constraint satis'action& Walt7

algorithm.

;LP Ste,s in the ,rocess& syntactic ,rocessing& Semantic %nalysis& *iscourse an$

,ragmatic ,rocessing

IV %lanning

#ntro$uction to ,lanning& +om,onents o' a ,lanning systems& oal stack Planning& ;on

Linear ,lanning& )lock orl$& Hierarchical ,lanning& least commitment stratagy& ,lanning

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5e'erence :

1. %rti'icial #ntelligence -y Elaine 5ich an$ 3erin 3night. %rti'icial ;eural ;etork -y 3rishna Mehrotra& San=ay 5aika 3.

Mohon

>. #ntro$uction to arti'icial intelligence -y Eugane& +harniak 6re Mc *ermott4. P5"L",rogramming 'or %rti'icial #ntelligence -y #. uni'ication algorithm im,lementation

4. truth mentainance system using ,rolog

!. im,lementation o' minmax search ,roce$ure 'or game ,laying

C. ,assing metho$ im,lemetation using ,rolog

D. $e. stu$ents can -e gi

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