The complexity of Markov decision processes
Mathematics of Operations Research
The complexity of stochastic games
Information and Computation
The computational complexity of propositional STRIPS planning
Artificial Intelligence
Expressive equivalence of planning formalisms
Artificial Intelligence - Special volume on planning and scheduling
An algorithm for probabilistic planning
Artificial Intelligence - Special volume on planning and scheduling
Abstraction and approximate decision-theoretic planning
Artificial Intelligence
SFCS '83 Proceedings of the 24th Annual Symposium on Foundations of Computer Science
Exploiting structure in policy construction
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Two forms of dependence in propositional logic: controllability and definability
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Using caching to solve larger probabilistic planning problems
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Alternative essences of intelligence
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
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
Complexity of finite-horizon Markov decision process problems
Journal of the ACM (JACM)
Probabilistic Situation Calculus
Annals of Mathematics and Artificial Intelligence
Stochastic Boolean Satisfiability
Journal of Automated Reasoning
Polynomial-Length Planning Spans the Polynomial Hierarchy
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
CL '00 Proceedings of the First International Conference on Computational Logic
Nearly deterministic abstractions of Markov decision processes
Eighteenth national conference on Artificial intelligence
The size of MDP factored policies
Eighteenth national conference on Artificial intelligence
Reasoning about actions in a probabilistic setting
Eighteenth national conference on Artificial intelligence
On the undecidability of probabilistic planning and related stochastic optimization problems
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
Contingent planning under uncertainty via stochastic satisfiability
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
Equivalence notions and model minimization in Markov decision processes
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
When plans distinguish Bayes nets
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Proceedings of the 13th international conference on World Wide Web
State explosion in almost-sure probabilistic reachability
Information Processing Letters
A Logic-Based Approach to Finding Explanations for Discrepancies in Optimistic Plan Execution
Fundamenta Informaticae
Maintenance goals of agents in a dynamic environment: Formulation and policy construction
Artificial Intelligence
Encoding probabilistic causal model in probabilistic action language
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Using domain-configurable search control for probabilistic planning
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
On polynomial sized MDP succinct policies
Journal of Artificial Intelligence Research
The first probabilistic track of the international planning competition
Journal of Artificial Intelligence Research
The computational complexity of probabilistic planning
Journal of Artificial Intelligence Research
Computational complexity of planning and approximate planning in presence of incompleteness
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Updates, actions, and planning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Complexity of probabilistic planning under average rewards
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Computational complexity of planning with temporal goals
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Conformant plans and beyond: Principles and complexity
Artificial Intelligence
Semantic email: theory and applications
Web Semantics: Science, Services and Agents on the World Wide Web
The cog project: building a humanoid robot
Computation for metaphors, analogy, and agents
The complexity of plan existence and evaluation in robabilistic domains
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Survey A survey of computational complexity results in systems and control
Automatica (Journal of IFAC)
A Logic-Based Approach to Finding Explanations for Discrepancies in Optimistic Plan Execution
Fundamenta Informaticae
| Hi-index | 0.00 |
Many representations for probabilistic propositional planning problems have been studied. This paper reviews several such representations and shows that, in spite of superficial differences between the representations, they are "expressively equivalent," meaning that planning problems specified in one representation can be converted to equivalent planning problems in any of the other representations with at most a polynomial factor increase in the size of the resulting representation and the number of steps needed to reach the goal with sufficient probability. The paper proves that the computational complexity of determining whether a successful plan exists for planning problems expressed in any of these representations is EXPTIME-complete and PSPACE-complete when plans are restricted to take a polynomial number of steps.