Journal of Computer and System Sciences
Principles of artificial intelligence
Principles of artificial intelligence
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Extending Graphplan to handle uncertainty and sensing actions
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Contingency Selection in Plan Generation
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Planning and acting in partially observable stochastic domains
Artificial Intelligence
The *-minimax search procedure for trees containing chance nodes
Artificial Intelligence
Computing optimal policies for partially observable decision processes using compact representations
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Using CSP look-back techniques to solve real-world SAT instances
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Initial experiments in stochastic satisfiability
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Planning under uncertainty via stochastic satisfiability
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Stochastic Boolean Satisfiability
Journal of Automated Reasoning
Progressive Planning for Mobile Robots (A Progress Report)
Revised Papers from the International Seminar on Advances in Plan-Based Control of Robotic Agents,
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Deconstructing planning as satisfiability
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Engineering a conformant probabilistic planner
Journal of Artificial Intelligence Research
Conditional progressive planning under uncertainty
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Planning under continuous time and resource uncertainty: a challenge for AI
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Optimal limited contingency planning
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
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We describe two new probabilistic planning techniques-- c-MAXPLAN and ZANDER--that generate contingent plans in probabilistic propositional domains. Both operate by transforming the planning problem into a stochastic satisfiability problem and solving that problem instead. C-MAXPLAN encodes the problem as an E-MAJSAT instance, while ZANDER encodes the problem as an S-SAT instance. Although S-SAT problems are in a higher complexity class than E-MAJSAT problems, the problem encodings produced by ZANDER are substantially more compact and appear to be easier to solve than the corresponding E-MAJSAT encodings. Preliminary results for ZANDER indicate that it is competitive with existing planners on a variety of problems.