August 29. The nature of intelligence. Computational approaches to artificial intelligence. (Lecture notes in PostScript and Portable Document Format.)
Reading: Russell and Norvig, preface (pages vii-x), chapter 1 (pages 1-31) and sections 26.1 and 26.2 (pages 947-960).
September 1. ``Weak'' and ``strong'' AI.
Reading: Russell and Norvig, sections 26.3 and 26.4 (pages 960-967); ``Software engineering code of ethics and professional practice.''
September 3. Programming ethics. Ethical dilemmas in AI.
Reading: Russell and Norvig, chapter 2 (pages 32-58).
September 5. Agents.
Reading: Fogel and Bar, chapter 2.
September 8. Using CVS (Concurrent Versions System).
Reading: Russell and Norvig, sections 3.1 through 3.4 (pages 59-81).
September 10. Solving problems by searching.
Reading: Russell and Norvig, sections 3.5 through 3.7 (pages 81-93).
September 12. Improving searching algorithms.
Reading: Russell and Norvig, sections 4.1 and 4.2 (pages 94-110).
September 15. Heuristics.
Reading: Russell and Norvig, section 4.3 (pages 110-119).
September 17. Local search and optimization.
September 19. Simulated annealing.
September 22. Genetic algorithms.
Reading: Russell and Norvig, sections 4.4 through 4.6 (pages 119-136).
September 24. On-line search agents.
Reading: Russell and Norvig, chapter 5 (pages 137-160).
September 26. Constraint-satisfaction problems; backtracking.
Reading: Russell and Norvig, sections 6.1 and 6.2 (pages 161-167).
September 29. Adversarial search.
Reading: Russell and Norvig, section 6.3 (pages 167-171).
October 1. Alpha-beta pruning.
Reading: Russell and Norvig, sections 6.4 through 6.8 (pages 171-193).
October 3. Search under time constraints; games of chance.
Reading: Russell and Norvig, sections 7.1 through 7.4 (pages 194-211).
October 6. Knowledge and deductive reasoning; propositional logic.
Reading: Russell and Norvig, section 7.5 (pages 211-220).
October 8. Inference and theorem-proving in propositional logic.
Reading: Russell and Norvig, sections 7.6 through 7.8 (pages 220-239).
October 10. The Davis-Putnam algorithm.
Reading: Russell and Norvig, chapter 8 (pages 240-271).
October 13. First-order logic and knowledge representation.
Reading: Russell and Norvig, sections 9.1 and 9.2 (pages 272-280).
October 15. Unification.
Reading: Russell and Norvig, sections 9.3 through 9.6 (pages 280-319).
October 17. Resolution.
Reading: Russell and Norvig, sections 10.1 through 10.3 (pages 320-340).
October 27. Knowledge representation.
Reading: Russell and Norvig, sections 10.4 through 10.6 (pages 341-354).
October 29. Semantic networks.
Reading: Russell and Norvig, sections 10.7 through 10.9 (pages 355-374).
October 31. Reasoning with defaults; exceptions; truth-maintenance systems.
Reading: Russell and Norvig, sections 11.1 through 11.2 (pages 375-387).
November 3. Planning and search.
Reading: Russell and Norvig, section 11.3 (pages 387-395).
November 5. Partial-order planning.
Reading: Russell and Norvig, section 11.4 (pages 395-402).
November 7. Planning graphs.
Reading: Russell and Norvig, chapter 13 (pages 462-491).
November 10. Probability; Bayes's rule.
Reading: Russell and Norvig, chapter 14 (pages 492-536).
November 12. Probabilistic reasoning.
Reading: Russell and Norvig, chapter 16 (pages 584-612).
November 14. Making decisions.
Reading: Russell and Norvig, chapter 17 (pages 613-648).
November 17. Markov decision processes.
November 19. The Bellman algorithm.
Reading: Russell and Norvig, chapter 18 (pages 649-677).
November 21. Learning.
Reading: Russell and Norvig, sections 19.1 through 19.3 (pages 678-694).
November 24. Learning with background knowledge.
Reading: Russell and Norvig, sections 19.4 through 19.6 (pages 694-711).
November 26. Inductive reasoning.
Reading: Russell and Norvig, sections 20.1 and 20.2 (pages 712-724).
December 1. Bayesian learning.
Reading: Russell and Norvig, sections 20.3 and 20.4 (pages 724-736).
December 3. Learning with hidden variables.
Reading: Russell and Norvig, sections 20.5 through 20.8 (pages 736-762).
December 5. Neural networks.
Reading: Russell and Norvig, chapter 21 (pages 763-789).
December 8. Reinforcement learning.
Reading: Russell and Norvig, chapter 25 (pages 901-946).
December 10. Robotics.
December 12. Summary and review; student evaluations.
December 17, 9 a.m. Final examination.
This document is available on the World Wide Web as
http://www.cs.grinnell.edu/~stone/courses/artificial-intelligence/schedule-of-topics.xhtml
created August 28, 2003
last revised November 19, 2003