Prerequisites: CA 710
Outline:
1. Definitions – History – Intelligent Agents – Structure – Environment – Basic Agents - Formulating – Search Strategies – Intelligent search – Game playing as search. Knowledge Based Agents.
2. Representation – Logic – First order logic – Reflex Agent – Building a knowledge base – General Ontology – Inference – Logical Recovery - Planning Agents.
3. Situational Calculus – Representation of Planning – Partial order Planning – Practical planners – Conditional Planning – Replanning Agents - Agents and uncertainty.
4. Acting under uncertainty – Probability Bayes Rule and use – Belief Networks – Utility Theory – Decision Network – Value of information – Decision Theoretic Agent Design - Higher level agents.
5. Learning agents – General Model – Inductive learning – Learning Decision Trees – Reinforcement Learning – knowledge in learning – Communicative agents – Types of Communicating agents – Future of AI.
Books:
1. Nils.J.Nilsson, Principles of Artificial Intelligence, Narosa Publishing House, 1992.
2. Jeffrey M.Bradshaw, An Introduction to Software Agents, MIT Press, USA 1997.
