The knowledge complexity of interactive proof-systems
STOC '85 Proceedings of the seventeenth annual ACM symposium on Theory of computing
The complexity of Markov decision processes
Mathematics of Operations Research
A survey of algorithmic methods for partially observed Markov decision processes
Annals of Operations Research
The computational complexity of propositional STRIPS planning
Artificial Intelligence
An algorithm for probabilistic planning
Artificial Intelligence - Special volume on planning and scheduling
Distinguishing tests for nondeterministic and probabilistic machines
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
Probabilistic Two-Way Machines
Proceedings on Mathematical Foundations of Computer Science
MFCS '97 Proceedings of the 22nd International Symposium on Mathematical Foundations of Computer Science
Complexity Issues in Markov Decision Processes
COCO '98 Proceedings of the Thirteenth Annual IEEE Conference on Computational Complexity
Algorithms for sequential decision-making
Algorithms for sequential decision-making
Introduction to probabilistic automata (Computer science and applied mathematics)
Introduction to probabilistic automata (Computer science and applied mathematics)
On the complexity of space bounded interactive proofs
SFCS '89 Proceedings of the 30th Annual Symposium on Foundations of Computer Science
The computational complexity of probabilistic planning
Journal of Artificial Intelligence Research
Probabilistic propositional planning: representations and complexity
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Survey A survey of computational complexity results in systems and control
Automatica (Journal of IFAC)
Complexity of finite-horizon Markov decision process problems
Journal of the ACM (JACM)
The Complexity of Decentralized Control of Markov Decision Processes
Mathematics of Operations Research
Reinforcement learning for POMDPs based on action values and stochastic optimization
Eighteenth national conference on Artificial intelligence
The size of MDP factored policies
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
Solving factored MDPs using non-homogeneous partitions
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
Point-Based Value Iteration for Continuous POMDPs
The Journal of Machine Learning Research
Sequential Monte Carlo in reachability heuristics for probabilistic planning
Artificial Intelligence
A POMDP framework for coordinated guidance of autonomous UAVs for multitarget tracking
EURASIP Journal on Advances in Signal Processing - Special issue on signal processing advances in robots and autonomy
Value-function approximations for partially observable Markov decision processes
Journal of Artificial Intelligence Research
Nonapproximability results for partially observable Markov decision processes
Journal of Artificial Intelligence Research
On polynomial sized MDP succinct policies
Journal of Artificial Intelligence Research
Perseus: randomized point-based value iteration for POMDPs
Journal of Artificial Intelligence Research
Online planning algorithms for POMDPs
Journal of Artificial Intelligence Research
AEMS: an anytime online search algorithm for approximate policy refinement in large POMDPs
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Complexity of probabilistic planning under average rewards
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Conditional planning in the discrete belief space
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
IEEE Transactions on Wireless Communications
A POMDP approximation algorithm that anticipates the need to observe
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
A decision-theoretic formalism for belief-optimal reasoning
PerMIS '09 Proceedings of the 9th Workshop on Performance Metrics for Intelligent Systems
A Modified Memory-Based Reinforcement Learning Method for Solving POMDP Problems
Neural Processing Letters
Decentralized MDPs with sparse interactions
Artificial Intelligence
Evolving policies for multi-reward partially observable markov decision processes (MR-POMDPs)
Proceedings of the 13th annual conference on Genetic and evolutionary computation
The complexity of decentralized control of Markov decision processes
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Vector-space analysis of belief-state approximation for POMDPs
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
Teaching memoryless randomized learners without feedback
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Quantitative access control with partially-observable Markov decision processes
Proceedings of the second ACM conference on Data and Application Security and Privacy
Survey A survey of computational complexity results in systems and control
Automatica (Journal of IFAC)
On the Computational Complexity of Stochastic Controller Optimization in POMDPs
ACM Transactions on Computation Theory (TOCT)
Undecidability in epistemic planning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
A survey of multi-objective sequential decision-making
Journal of Artificial Intelligence Research
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We investigate the computability of problems in probabilistic planning and partially observable infinite-horizon Markov decision processes. The undecidability of the string-existence problem for probabilistic finite automata is adapted to show that the following problem of plan existence in probabilistic planning is undecidable: given a probabilistic planning problem, determine whether there exists a plan with success probability exceeding a desirable threshold. Analogous policy-existence problems for partially observable infinite-horizon Markov decision processes under discounted and undiscounted total reward models, average-reward models, and state-avoidance models are all shown to be undecidable. The results apply to corresponding approximation problems as well.