Handbook of theoretical computer science (vol. B)
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Hierarchical task network planning: formalization, analysis, and implementation
Hierarchical task network planning: formalization, analysis, and implementation
Automatic OBDD-based generation of universal plans in non-deterministic domains
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Complexity and Approximation: Combinatorial Optimization Problems and Their Approximability Properties
Planning with Sensing for a Mobile Robot
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Strong Cyclic Planning Revisited
ECP '99 Proceedings of the 5th European Conference on Planning: Recent Advances in AI Planning
Planning with a language for extended goals
Eighteenth national conference on Artificial intelligence
Weak, strong, and strong cyclic planning via symbolic model checking
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
SAT-based planning in complex domains: concurrency, constraints and nondeterminism
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
STRIPS: a new approach to the application of theorem proving to problem solving
IJCAI'71 Proceedings of the 2nd international joint conference on Artificial intelligence
Complexity results for planning
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Heuristic search + symbolic model checking = efficient conformant planning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Proof Systems for Planning Under Cautious Semantics
Minds and Machines
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PKS is the framework for planning with incomplete information and sensing recently introduced by Bacchus and Petrick [Proc. KR'98, pp. 432-443]. The fact that PKS generalizes STRIPS to domains with incomplete information and sensing opens up the possibility of proposing it as a reference for comparisons with other formalisms that approach the problem from different perspectives. To this end we first provide a formal semantics for PKS, then analyze and extend it. The formal definition of the extended PKS entails the identification of a number of properties of this planning framework. In particular, we prove that for any finite instance of the PKS planning problem the reachable states are finite; on the basis of this result we propose an improved planning algorithm that is not only sound, as the one proposed by Petrick and Bacchus [Proc. AIPS'02, pp. 212-221], but also complete. We extend PKS to include conditional plans with cycles and introduce the distinction between different classes of solutions: strong, strong cyclic, weak acyclic and weak cyclic. In contrast with current belief, we prove that some weak acyclic solutions are more likely to succeed for a limited execution than some strong cyclic solutions, revealing the lack of a method for judging the quality of different solutions. Finally, we introduce a quality measure for solutions of any class, and a quantitative method for comparing them.