16. Explanation and diagnosis

B&L Ch 13

Leader 1: Janson Orson

Leader 2: Thomas Thomas

17. SAT-modulo theories

C. Barrett, R. Sebastiani, S. A. Seshia, & C. Tinelli, Satisfiability Modulo Theories, in A. Biere, H. van Maaren, M. Heule and Toby Walsh, Eds., Handbook of Satisfiability, IOS Press, 2009.(See course reserves)

Leader 1: Aaron Gorenstein

Leader 2: Erin Brady

19. Reasoning about the knowledge of multiple agents

J. Halpern, Reasoning about knowledge: a survey, in D. Gabbay, C. J. Hogger, and J. A. Robinson, Eds.,Handbook of Logic in Artificial Intelligence and Logic Programming, Vol. 4, Oxford University Press, 1995.

Leader 1: Andrew Reinders

Leader 2: Ashker Ibne Mujib

20. Limited and approximate inference

Liu, Y., Lakemeyer, G., and Levesque, H., A logic of limited belief for reasoning with disjunctive information, Proc. of the KR-2004 Conference, Whistler, BC, 2004.

H. Kautz and B. Selman, A General Framework for Knowledge Compilation, Proceedings of the First World Conference on the. Fundamentals of Artificial Intelligence, Paris, 1991.

Leader 1: Lingxiang Xiang

Leader 2: Shu Mao

21. Bayesian networks

B&L 12.1-12.4; R&N 14.5

Leader 1: Adam Purtee

Leader 2: Shantonu Hossain

22. Bayesian reasoning using MAX-SAT and model-counting

J. D. Park, Using Weighted MAX-SAT Engines to Solve MPE, Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-02), Edmonton, Alberta, 2002, pages 682-687.

T. Sang, P. Beame, & H. Kautz., Solving Bayesian Networks by Weighted Model Counting, Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05), Pittsburgh, PA, 2005.

Leader 1: Shuo Yang

Leader 2: Jang (Karl) Sun Lee

23. Markov logic

P. Domingos & D. Lowd, Markov Logic: An Interface Layer for Artificial Intelligence, Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool, 2009. (See course reserves)

Leader 1: Anna Loparev

Leader 2: Walter Lasecki

24. Markov logic, continued