Teaching Scheme (in Hours)
| Theory |
Tutorial |
Practical |
Total |
| 4 |
0 |
2 |
6 |
Subject Credit : 6
Examination Scheme (in Marks)
Theory
ESE (E)
|
Theory
PA (M)
|
Practical
ESE Viva (V)
|
Practical
PA (I)
|
Total
|
| 70 |
30 |
30 |
20 |
150 |
Syllabus Content
Unit-1: What is AI?
The AI Problems, The Underlying Assumption, What Is An AI Techniques, The Level Of The Model, Criteria For Success, Some General References, One Final Word.
Unit-2: Problems, State Space Search & Heuristic Search Techniques
Defining The Problems As A State Space Search, Production Systems, Production Characteristics, Production System Characteristics, And Issues In The Design Of Search Programs, Additional Problems. Generate-And-Test, Hill Climbing, Best-First Search, Problem Reduction, Constraint Satisfaction, Means-Ends Analysis
Unit-3: Knowledge Representation Issues
Representations And Mappings, Approaches To Knowledge Representation
Unit-4: Using Predicate Logic
Representation Simple Facts In Logic, Representing Instance And Isa Relationships, Computable Functions And Predicates, Resolution.
Unit-5: Representing Knowledge Using Rules
Procedural Versus Declarative Knowledge, Logic Programming, Forward Versus Backward Reasoning
Unit-6: Symbolic Reasoning Under Uncertainty
Introduction To Nonmonotonic Reasoning, Logics For Non- onotonic Reasoning.
Unit-7: Statistical Reasoning
Probability And Bays’ Theorem, Certainty Factors And Rule-Base Systems, Bayesian Networks, DempsterShafer Theory, Fuzzy Logic.
Unit-8: Weak Slot-and-Filler Structures
Semantic Nets, Frames.
Unit-9: Strong Slot-and-Filler Structures
Conceptual Dependency, Scripts, CYC
Unit-10: Game Playing: Overview, And Example Domain
Overview, MiniMax, Alpha-Beta Cut-off, Refinements, Iterative deepening, The Blocks World, Components Of A Planning System, Goal Stack Planning, Nonlinear Planning Using Constraint Posting, Hierarchical Planning, Reactive Systems, Other Planning Techniques.
Unit-11: Understanding
What is understanding? , What makes it hard?, As constraint satisfaction
Unit-12: Natural Language Processing
Introduction, Syntactic Processing, Semantic Analysis, Semantic Analysis, Discourse And Pragmatic Processing, Spell Checking
Unit-13: Connectionist Models
Introduction: Hopfield Network, Learning In Neural Network, Application Of Neural Networks, Recurrent Networks, Distributed Representations, Connectionist AI And Symbolic AI
Unit-14: Introduction to Prolog
Introduction To Prolog: Syntax and Numeric Function, Basic List Manipulation Functions In Prolog, Functions, Predicates and Conditional, Input, Output and Local Variables, Iteration and Recursion, Property Lists and Arrays, Miscellaneous Topics, LISP and Other AI Programming Languages.
Reference Books
| Sr. |
Title |
Author |
Publication |
Amazon Link |
| 1 |
Artificial Intelligence |
Elaine Rich And Kevin Knight |
Tata Mcgraw-Hill |
|
| 2 |
Artificial Intelligence: A Modern Approach, |
Stuart Russel, Peter Norvig, |
PHI |
|
| 3 |
Introduction to Prolog Programming |
Carl Townsend |
|
|
| 4 |
PROLOG Programming For Artificial Intelligence |
Ivan Bratko |
|
|
| 5 |
Programming with PROLOG |
Klocksin and Mellish |
|
|
