6.034 | Fall 2010 | Undergraduate

Artificial Intelligence


Unless otherwise noted, the readings below are from the course textbook:

Winston, Patrick Henry. Artificial Intelligence. 3rd ed. Addison-Wesley, 1992. ISBN: 9780201533774.

Additional resources, where relevant, are listed with the respective Lecture Videos under the “Related Resources” tab.

1 Introduction and scope  
2 Reasoning: goal trees and problem solving Application: Symbolic Integration, p. 61.
3 Reasoning: goal trees and rule-based expert systems Chapter 3, pp. 53–60.
4 Search: depth-first, hill climbing, beam Chapter 4
5 Search: optimal, branch and bound, A* Chapter 5
6 Search: games, minimax, and alpha-beta Chapter 6
7 Constraints: interpreting line drawings Chapter 12
8 Constraints: search, domain reduction  
9 Constraints: visual object recognition Chapter 26
10 Introduction to learning, nearest neighbors Chapter 19
11 Learning: identification trees, disorder Chapter 21
12 Learning: neural nets, back propagation Neural net notes (PDF)
13 Learning: genetic algorithms Chapter 25
14 Learning: sparse spaces, phonology Yip, Kenneth, and Gerald Jay Sussman. “Sparse Representations for Fast, One-Shot Learning.” (PDF)
15 Learning: near misses, felicity conditions Chapter 16
16 Learning: support vector machines Support vector machine slides (PDF)
17 Learning: boosting

Boosting notes (PDF) (Courtesy of Patrick Winston and Luis Ortiz. Used with permission.)

Schapire, Robert. “The Boosting Approach to Machine Learning: An Overview.” MSRI Workshop on Nonlinear Estimation and Classification, 2002. (PDF)

18 Representations: classes, trajectories, transitions Chapter 9
19 Architectures: GPS, SOAR, Subsumption, Society of Mind

Lehman, Jill, John Laird, and Paul Rosenbloom. “A Gentle Introduction to Soar, An Architecture for Human Cognition: 2006 Update.” (PDF)

Brooks, Rodney. “Intelligence Without Representation.” Artificial Intelligence 47 (1991): 139–59.

Winston, Patrick Henry. “S3, Taking Machine Intelligence to the Next, Much Higher Level.” (PDF)

20 The AI business  
21 Probabilistic inference I  
22 Probabilistic inference II Probabilistic inference notes (PDF)
23 Model merging, cross-modal coupling, course summary Coen, Michael. “Self-Supervised Acquisition of Vowels in American English.” (PDF - 4.8MB) AAAI Proceedings of the 21st National Conference on Artificial Intelligence 2 (2006).

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As Taught In
Fall 2010
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