Artificial intelligence and mathematical theory of computation
An algorithm for probabilistic least-commitment planning
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Abstraction and approximate decision-theoretic planning
Artificial Intelligence
The independent choice logic for modelling multiple agents under uncertainty
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Solving very large weakly coupled Markov decision processes
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Reinforcement learning with hierarchies of machines
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Some contributions to the metatheory of the situation calculus
Journal of the ACM (JACM)
Between MDPs and semi-MDPs: a framework for temporal abstraction in reinforcement learning
Artificial Intelligence
Stochastic dynamic programming with factored representations
Artificial Intelligence
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Neuro-Dynamic Programming
Theoretical Results on Reinforcement Learning with Temporally Abstract Options
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Advances in Neural Information Processing Systems 5, [NIPS Conference]
Decision-Theoretic, High-Level Agent Programming in the Situation Calculus
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Dynamic Programming
Hierarchical reinforcement learning with the MAXQ value function decomposition
Journal of Artificial Intelligence Research
An on-line decision-theoretic Golog interpreter
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Symbolic dynamic programming for first-order MDPs
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Flexible decomposition algorithms for weakly coupled Markov decision problems
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
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Markov decision processes (MDPs) have become the de facto standard model for decision-theoretic planning problems. However, classic dynamic programming algorithms for MDPs [22] require explicit state and action enumeration. For example, the classical representation of a value function is a table or vector associating a value with each system state; such value functions are produced by iterating over the state space. Since state spaces grow exponentially with the number of domain features, the direct application of these models to AI planning problems is limited. Furthermore, for infinite and continuous spaces, such methods cannot be used without special knowledge of the form of the value function or optimal control policy.