Arizona State University

Welcome to CSE 571, Fall 99 home page


Pointers to reference articles for this class.

The Texas action group site with pointers to many AI language related papers


FTP site for the planning contest domains.

PDDL: planning domain definition language.

Papers by Hector Geffner. (For the search and POMDP/MDP parts).

U. of Toronto Cognitive Robotics group home page

Handouts of slides for this class.

Handout 1 -- Languages for AI (postscript file)

Handout 2 (version 2) -- Search and its role in planning (postscript file)

Handout 2 (version 3) -- Search and its role in planning -- contains MDP/POMDP stuff (postscript file)

Handout 3 -- Logic, KR and model based planning (version 3, postscript file)

Handout 4 -- Probability, Bayes nets and causality (version 1, postscript file)

Test II (part a) -- postscript file

Test II (part b) -- postscript file

Partial list of papers that are used in the class.

On languages for planning and reasoning about actions

M. Gelfond and V. Lifschitz, Representing action and change by logic programs, Journal of Logic Programming, Vol. 17, pp. 301-321, 1993.

C. Baral and M. Gelfond, Reasoning about effects of concurrent actions, Journal of Logic Programming vol. 31, pp. 85-118, 1997.

G. N. Kartha and V. Lifschitz, "Actions with indirect effects (preliminary report)," in Proceedings of the Fourth International Conference on Principles of Knowledge Representation and Reasoning, pp. 341-350, 1994.

H. Turner, Representing actions in logic programs and default theories: A situation calculus approach, Journal of Logic Programming, Vol. 31, pp. 245-298, 1997.

On role of heuristic search in planning.

HSP: Heuristic Search planner. Bonet and Geffner. Entry at the AIPS-98 planning competition, Pittsburgh 6/98.

Planning as heuristic search: new results. B. Bonet and H. Geffner. Proc. of European Conference on planning, 1999, Durham, UK.

On role of real time search in solving MDPs and POMDPS.

Solving large POMDPs using real time dynamic programming. H. Geffner and B. Bonet. Working notes. Fall AAAI symposium on POMDPs. 1998.

Planning with MDPs and POMDPs: slides. H. Geffner. (joint work with B. Bonet.) Invited talk at ECAI 98 workshop on decision theory meets AI. Brighton, UK, 8/98.

Learning Sorting and Decision Trees with POMDPs B. Bonet and H. Geffner. Proceedings International Conference on Machine Learning (ICML-98), Madison, WI, 7/98.

Logic and its role in reasoning about actions and model based planning.

Knowledge in Action: Logical Foundation for describing and implementing dynamical systems. Ray Reiter. (Chapters 1-4)

Computing Circumscription. V. Lifschitz. Ninth International Conference on Artificial Intelligence, pp 121-127, 1985.

Planning as satisfiability. H. Kautz and B. Selman. Proc. of European conference on Artificial Intelligence, 1992, pages 359-363.

Encoding plans in propositional logic. H. Kautz, D. McAllester, and B. Selman. Proc. of Knowledge Representation and Reasoning 1996, pages 374-384.

(For the above two papers, check Bart Selman's site at CS Dept of Cornell University.)

Probability, Bayes net, and causality: predictions, effect of actions, and countefactuals.

Judea Pearl's home page.

Causality: models, reasoning and inference. Judea Pearl. Cambridge University Press.

Reasoning with Cause and Effect. Judea Pearl. IJCAI 99. (available through Judea's home page)

A probabilistic calculus of actions. Judea Pearl.UAI 94. (available through Judea's home page.)