ARTIFICIAL INTELLIGENCE
L T P C
Theory 3 0 0 3
UNIT I: INTRODUCTION TO ARTIFICIAL
INTELLIGENCE 9
Introduction to Al – Definition – Goals of Al –
Applications of Al – History of Al – Types of Al –
Components of Al – Human vs Machine intelligence
Agents – Rationality – Structure of Agents – Problem
Solving Agents – Types of Agents – Environments-Nature of
Environments
UNIT II: PROBLEM SOLVING USING SEARCH
TECHNIQUES 9
Search Algorithms: Evaluating Search Strategies –
Breadth-first search, Uniform cost search, Depth – first search,
Bidirectional Search.
Heuristic Search Strategies: Best First Search, Heuristic
Search, A* Search
UNIT III: KNOWLEDGE REPRESENTATION AND
OPTIMIZATION TECHNIQUES 9
Knowledge Representation: Knowledge-Based Agents,
Logic, Propositional Logic: A Very Simple Logic, Ontological
Engineering, Categories and Objects, Events, Mental Events
and Mental Objects, Reasoning Systems for Categories
Optimization Algorithms: Hill Climbing, Local Beam
Search and Genetic Algorithm
UNIT IV: GAME PLAYING AND CONSTRAINT
SATISFACTION PROBLEMS 9
Game Theory: The Mini-Max search – Alpha-Beta
Search – Introduction to CSPs Constraint Networks – Binary
and Non-Binary Constraints – Constraint Propagation –
Backtracking Search for CSP–Local for CSP–Structure of CSP.
UNIT V: INTELLIGENT AGENTS 9
Knowledge-Based Agents – Propositional Logic –
Propositional Theorem Proving – Propositional Model
Checking – Agents Based on Propositional Logic.
Architecture for Intelligent Agents – Agent
communication – Argumentation among Agents.
TOTAL PERIODS 45