The computational complexity of propositional STRIPS planning
Artificial Intelligence
Fast planning through planning graph analysis
Artificial Intelligence
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
A Computing Procedure for Quantification Theory
Journal of the ACM (JACM)
Artificial Intelligence
A machine program for theorem-proving
Communications of the ACM
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Polynomial-Length Planning Spans the Polynomial Hierarchy
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
Planning as Satisfiability in Nondeterministic Domains
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Combining the Expressivity of UCPOP with the Efficiency of Graphplan
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
A logic programming approach to knowledge-state planning, II: the DLVk system
Artificial Intelligence
Conformant planning via symbolic model checking and heuristic search
Artificial Intelligence
Conformant planning via symbolic model checking
Journal of Artificial Intelligence Research
The FF planning system: fast plan generation through heuristic search
Journal of Artificial Intelligence Research
Constructing conditional plans by a theorem-prover
Journal of Artificial Intelligence Research
A simplifier for propositional formulas with many binary clauses
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Towards Efficient Belief Update for Planning-Based Web Service Composition
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Probabilistic planning via heuristic forward search and weighted model counting
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
Compiling uncertainty away in conformant planning problems with bounded width
Journal of Artificial Intelligence Research
Compiling Uncertainty Away in Non-Deterministic Conformant Planning
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
On the impact of belief state representation in planning under uncertainty
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
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Conformant planning is the task of generating plans given uncertainty about the initial state and action effects, and without any sensing capabilities during plan execution. The plan should be successful regardless of which particular initial world we start from. It is well known that conformant planning can be transformed into a search problem in belief space, the space whose elements are sets of possible worlds. We introduce a new representation of that search space, replacing the need to store sets of possible worlds with a need to reason about the effects of action sequences. The reasoning is done by implication tests on propositional formulas in conjunctive normal form (CNF) that capture the action sequence semantics. Based on this approach, we extend the classical heuristic forward-search planning system FF to the conformant setting. The key to this extension is an appropriate extension of the relaxation that underlies FF's heuristic function, and of FF's machinery for solving relaxed planning problems: the extended machinery includes a stronger form of the CNF implication tests that we use to reason about the effects of action sequences. Our experimental evaluation shows the resulting planning system to be superior to the state-of-the-art conformant planners MBP, KACMBP, and GPT in a variety of benchmark domains.