Prerequisite: Instructor's permission
Concepts of knowledge and learning in intelligent agents; Structure of agents; Knowledge representation paradigms; Inference and decision systems; Production systems. Problem solving by search; Graph search strategies; Local search; Constraint satisfaction problems and strategies.
Agents based on professional logic; Inference in first order logic; Forward chaining and backward chaining strategies; Resolution; Inference in Prolog; Constraint Logic; Programming; Adversarial search.
Representation of actions, events and time; Situation calculus; Semantic networks; Planning with state space search; Partial Order Planning; Planning Graphs; Conditional planning; Multi-agent planning; Large constraint directed scheduling systems; Reactive scheduling systems.
Inference in Bayesian networks; Other approaches to uncertain reasoning; Probabilistic reasoning over time; Hidden Markov models; Kalman filtering; Partially observable Markov decision processes; Learning decision trees; Ensemble learning.
Explanation based learning; Inductive logic programming; Reinforcement learning of environment and optimal control policy under uncertainty.
- S. Russell and P. Norvig (2003), Artificial Intelligence: A modern approach. 2nd Edition, Pearson Education Asia
- M. Stefik (1995), Introduction to Knowledge systems, Academic Press/Morgan Kaufmann
- A. A. Hopgood (1993), Knowledge based Systems for Engineers and Scientists CRC Press Inc., Boca Ration, Florida
- R. Froast (1986), Introduction to Expert Systems, Collins, London.
- P. Jackson (1999), Introduction to Expert Systems, Addison Wesley Longman Ltd; also reprinted by Pearson Education Asia Ltd.
- N. J. Nilsson (1998), Artificial Intelligence: A new synthesis, Harcourt Asia and Morgan Kaufmann.
- J. F. Sowa (2000), Knowledge Representation: Logical, Philosophical and Computational Foundations, Thomson Brooks/Cole and Vikas Publishing House
- I. Bratco (2001), Prolog: Programming for artificial intelligence, '3rd Edition, Pearson Education Asia.