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ARTIFICIAL INTELLIGENCE SYLLABUS
Module 1 12Hrs
What is Artificial Intelligence? AI Technique, Level of the Model,Problem Spaces, and Search: Defining
the Problem as a State Space Search, Production Systems, Problem Characteristics, Production System
Characteristics, Issues in the Design of Search Programs. Heuristic Search Techniques: Generate-and-
Test, Hill Climbing, Best-first Search, Problem Reduction, Constraint Satisfaction, Means-ends
Analysis, Knowledge Representation: Representations and Mappings, Approaches to Knowledge
Representation, Using Predicate Logic: Representing Simple Facts in Logic, Representing Instance and
ISA Relationships, Computable Functions and Predicates, Resolution, Natural Deduction.Using Rules:
Procedural Versus Declarative Knowledge, Logic Programming, Forward Versus Backward Reasoning,
Matching, Control Knowledge.Symbolic Reasoning Under Uncertainty: Introduction to Nonmonotonic
Reasoning, Logics for Nonmonotonic Reasoning, Implementation Issues, Augmenting a Problem-solver,
Depth-first Search, Breadthfirst Search.Weak and Strong Slot-and-Filler Structures: Semantic Nets,
Frames, Conceptual Dependency Scripts, CYC.
Module 2 10Hrs
Game Playing: The Minimax Search Procedure, Adding Alpha-beta Cutoffs, Iterative Deepening.Planning:
The Blocks World, Components of a Planning System, Goal Stack Planning, Nonlinear Planning Using
Constraint Posting, Hierarchical PlanningOther Planning Techniques.Understanding: What is
Understanding, What Makes Understanding Hard?, Understanding as Constraint Satisfaction.Natural
Language Processing: Introduction, Syntactic Processing, Semantic Analysis, Discourse and Pragmatic
Processing, Statistical Natural Language Processing, Spell Checking.
Module 3 8Hrs
Learning: Rote Learning, learning by Taking Advice, Learning in Problem-solving, Learning from
Examples: Induction, Explanation-based Learning, Discovery, Analogy, Formal Learning Theory, Neural
Net Learning and Genetic Learning. Expert Systems: Representing and Using Domain Knowledge, Expert
System Shells, Explanation, Knowledge Acquisition.
Text Book:
1. Elaine Rich, Kevin Knight, & Shivashankar B Nair, Artificial Intelligence, McGraw Hill, 3rd ed.,2009
References:
1) Introduction to Artificial Intelligence & Expert Systems, Dan W Patterson, PHI.,2010
2) S Kaushik, Artificial Intelligence, Cengage Learning, 1st ed.2011