Readings
A good place for starting Python is actually the on-line Python
tutorial. The Python language is available for Windows, Mac and Linux/Unix.
Books (required)
Russell, S., and Norvig, P., (2002).
Artificial Intelligence: A Modern Approach.
Prentice Hall.
Books (recommended)
Sutton, R. S., and Barto, A. G., (1998).
Reinforcement Learning.
Cambridge, Mass.: MIT Press.
Pearl, J., (1984). Heuristics: Intelligent Search Strategies for
Computer Problem-Solving. Addison Wesley. A very interesting
and unconventional book discussing a large number of interesting
questions and deep issues connected with heuristics used in classical
AI. Some prior experience with AI search methods is probably useful
before reading this book.
Pearl, J., (2000). Causality: Models, Reasoning and
Inference. Cambridge, UK: Cambridge University Press.
Luger, G., and Stubblefield, W., (1997). Artificial Intelligence:
Structures and Strategies for Complex Problem Solving.
Addison-Wesley. A modern approach.
Further reading suggestions
Lungarella, M., Iida, F., Bongard, J., and Pfeifer, R., editors,
Proc. 50th Anniversary Summit of Artificial Intelligence.
Springer-Verlag: Berlin, Heidelberg, New York.
Saygin, A., Cicekli, I., and Akman, V., (2000).
Turing Test: 50 Years Later.
Minds and Machines, 10(4):463-518.
Hofstadter, D., (1999). Gödel Escher Bach: An Eternal Golden
Braid. Basic Books Inc. 20th edition.
Nilsson, N., (1998). AI: A New Synthesis. Morgan Kauffman.
A new book from one of the most important classical AI
authors.
Selected readings from Proceedings of Conferences and Series:
International Joint Conference on Artificial Intelligence (IJCAI);
American Association for Artificial Intelligence (AAAI); Artificial
Intelligence and Simulation of Behaviour (AISB); European Conference
on Artificial Intelligence (ECAI); Springer Lecture Notes on
Artificial Intelligence (LNAI).
Papers and other Material
William Freeman, e.g. "Constructing Free Energy Approximations and Generalized Belief Propagation Algorithms"
Jack Breese,
Daphne Koller: "Bayesian Networks and Decision-Theoretic Reasoning for
Artificial Intelligence"
Research at the University of Hertfordshire
Check out our work on Artificial
Intelligence, Artificial Life and Information Theory for Intelligent
Information Processing
Last changed at Mon Jan 21 22:42:55 2008 by D. Polani
Department of Computer Science