Prerequisites : Knowledge of any advance programming language

 

Course Content:

 

Unit 1

Introduction: What is AI? Intelligent Agents: Agents and environment, Rationality, the nature of environment, the structure of agents. Problem-solving by search: Problem-solving agents, Example problems, searching for solution, Uninformed search strategies.

 

Unit 2

Informed Search and Exploration: Informed search strategies, Heuristic functions, On-line search agents and unknown environment. Logical Agents: Knowledge-based agents, The wumpus world, Logic, propositional logic, Reasoning patterns in propositional logic, Effective propositional inference, Agents based on propositional logic

 

Unit 3

First-Order Logic: Representation revisited, Syntax and semantics of first-order logic, Using first-order logic, Knowledge engineering in first-order logic. Interference in First-order Logic: Propositional versus first-order inference, Unification and lifting, Forward chaining, Backward chaining, Resolution.

 

Unit 4

Planning: The Planning problem, planning with state-space approach, Planning graphs, Planning with propositional logic. Uncertainty: Acting under uncertainty, Basic probability Notations, Inference using full joint distributions, Independence, Bayes’ rule and its use. Learning from observations: Forms of Learning, Inductive learning, learning decision trees, Ensemble learning, Computational learning theory

 

Unit 5

Natural Language Processing: Introduction, syntactic processing, semantic Analysis, discourse and pragmatic processing, statistical natural language processing.

Genetic Algorithms: GA, Significance of genetic operators, Termination parameters, Niching and Speciation, Evolving Neural Networks, Theoretical grounding, Ant Algorithms.

AI: Present and Future: Peer reviews in class room on Advance Topics in AI, AI Programming Languages, Current state of art of AI and its future.

 

Text Book:

1. Stuart Russel, Peter Norvig: Artificial Intelligence - A Modern Approach, 2nd Edition, Pearson Education, 2012.

2. Elaine Rich, Kevin Knight, Shivashankar B Nair: Artificial Intelligence, 3rd Edition, Tata McGraw Hill, 2011.

 

Reference Books:

1. Nils J. Nilsson: Principles of Artificial Intelligence, First Edition, Elsevier, 2002.

2. Luger, G. F., & Stubblefield, W. A., Artificial Intelligence - Structures and Strategies for Complex Problem Solving. New York, NY: Addison Wesley, 5th edition (2005).