Part 3 Artificial Intelligence
A. Search Techniques
- Generate-and-Test approach
- Constrain-and-generate approach
- Uninformed search methods (depth-first, breadth-first, etc.)
- Branch-and-bound
- Informed search methods (best-first, beam, A*, etc.)
- Heuristics for informed search methods and constraint satisfaction problems
- Adversarial search techniques and games (Minimax, Alpha-Beta Pruning)
B. Knowledge Representation
- Semantic networks
- Frames
- Production rule systems
- Neural networks and genetic algorithms
C. Logic
- Propositional Logic
- First-order (predicate) logic
- Clausal form (including skolemization)
- Unification
- Resolution
D. Applications
- Expert systems
- Learning
- Constraints and propagation
- Planning
- Natural language processing
Textbooks
- G. F. Luger and W. Stubblefield, Artificial Intelligence, Third Edition, Addison-Wesley, 1998.
- S. Russell and P. Norvig, Artificial Intelligence - A Modern Approach (second edition), Prentice Hall, 2003.
- P. H. Winston, Artificial Intelligence, Addison Wesley, 1992.
- M. R. Genesereth and N. J. Nilsson, Logical Foundations of Artificial Intelligence, Morgan Kaufmann 1987.
- C. J. Hogger, Essentials of Logic Programming, Oxford UP 1990.
- B. Coppin, Artificial Intelligence, Jones and Bartlett, 2004.
Note
Russell/Norvig is useful for areas A-D, but you may wish to consult Genesereth/Nilsson or Hogger to get more background on logic. Winston is very useful for all areas except logic.
