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Course Code:
MCA12
305

C
.
Artificial Intelligence & Expert Systems

UNIT
-
I:
What is Artificial Intelligence? The AI Problems


The Underlying Assumptions


What is an AI Techniques? Problems: Problems spaces and search


Defining the Problems
as a State Spa
ce Search


Production Systems


Problem Characteristics


Production System
Characteristics


Issues in the Design of Search Programmes.


UNIT II:
Generate


and
-
Test


Hill Climbing


Best
-
First Search


Problem Reduction


Constraint Satisfaction


Mea
ns


Ends


Analysis
-
Knowledge Representation issues:
Representation and Mappings


Approaches to Knowledge Representation


Issues in
Knowledge Representation


The Frame Problem


UNIT III:
Using predicate logic


Representing Simple facts in Logic


Rep
resenting
Instance and Is a relationships


Computable functions and Predicates


Resolutions


Natural Deductions


Representing Knowledge Using Rules: Procedural versus Declarative
Knowledge


Forward versus Backward Reasoning


Matching


Control Knowle
dge


UNIT IV:
Symbolic Reasoning under uncertainty


Introduction to Non Monotonic
Reasoning


Logics for Non Monotonic Reasoning


Implementation issues


Augmenting a
Problem solver


Implementation : Deapth


First Search


Implementation : Breadth


F
irst
Search


Statistical reasoning


Bayesian Networks


Fuzzy Logic
-

Learning: What is
learning?


Rote Learning


Learning by taking advice


Learning in Problem Solving


UNIT V:
Connectionist Models


Introduction


Hopfield Networks


Learning in Neu
ral
Networks


Applications of Neural Networks


Expert Systems


Representing and Using
Domain Knowledge


Expert System Shells


Explanation


Knowledge acquisition


Text Book:

Artificial Intelligence, Elaine Rich, Kevin Knight, 2/e, TataMcGraw Hill Pu
blishing Ltd.,
-

New Delhi, 1991

Chapters: 1.1


1.3, 2.3, 4.5, 6.7, 8.3


8.5, 17.1


17.4, 18.1


18.3 & 20


Reference Books:

1. Introduction to Artificial Intelligence and Expert Systems, Dan W.Patterson, Prentice Hall
of India, New Delhi, 1992

2. A
rtificial Intelligence, A Modern Approach, Stuart J. Russell and Peter Norvig, Pearson
Education, reprint 2003.

3. Introduction to Expert Systems, 3/e, Peter Jackson, Pearson Education, Reprint 2003

4. Artificial Intelligence, A New Synthesis, Nils J. Ni
lsson Harcourt Asia Pvt. Ltd., 1998

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