CS 540 - Introduction to Artificial Intelligence Section 1 Spring 2013

CS 540 Reading Assignments

• 5/6: Chapters 8.1 - 8.3
• 4/29: Chapters 7.1, 7.3 - 7.5
• 4/24: Chapter 18.10
  Optional: Eigenfaces for recognition" by M. Turk and A. Pentland, Journal of Cognitive Neuroscience 3(1), 1991, 71-86 (this is NOT required reading)
• 4/15: Chapter 15.1 - 15.3, 23.5, and "Markov models and hidden Markov models: A brief tutorial" by E. Fosler-Lussier, Technical Report TR-98-041, Int. Computer Science Institute, University of California, Berkeley, 1998
• 4/12: Optional: "Bayesian networks without tears" by E. Charniak, AI Magazine, Winter 1991, 50-63 (this is NOT required reading)
• 4/12: Chapter 14.1, 14.2, 14.4
• 4/3: Chapter 13
  Optional articles about misuse of probability for making inferences:
  • "Inferences about testosterone abuse among athletes" by D. Berry and L. Chastain, Chance 17(2), 2004, 8-11
  • "Justice flunks math" by L. Schneps and C. Colmez, New York Times, March 26, 2013
• 3/20: Chapter 18.3 and 18.4
  Optional: Decision tree demo at AIxploratorium
• 3/15: Chapter 18.9 and "Support vector machines" edited by M. Hearst, IEEE Intelligent Systems, July/August 1998, 18-28
• 3/1: Chapter 18.6.3, 18.6.4 and 18.7
• 2/27: Chapter 18.1 and 18.2
• 2/25: Chapter 1: Introduction to statistical machine learning by X. Zhu and A. Goldberg, from Introduction to Semi-Supervised Learning, Morgan and Claypool Publishers, 2009.
• 2/18: Chapter 6.1 - 6.4
• 2/11: Chapter 5.1 - 5.3
• 2/6: Chapter 4.1
  Optional: A nice app online for visualizing various search methods is here
• 2/1: Chapter 3.5 and 3.6
• 1/28: Chapter 3.1 - 3.4
• 1/23: Chapters 1 and 2 (focus on Sections 1.1, 2.1, 2.2 and 2.3; skim other sections) in the textbook (Artificial Intelligence: A Modern Approach, 3rd ed., S. Russell and P. Norvig, Prentice Hall, 2010)