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AI
2006
Springer
15 years 1 months ago
Belief Selection in Point-Based Planning Algorithms for POMDPs
Abstract. Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value funct...
Masoumeh T. Izadi, Doina Precup, Danielle Azar
NN
2010
Springer
187views Neural Networks» more  NN 2010»
14 years 4 months ago
Efficient exploration through active learning for value function approximation in reinforcement learning
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...
Takayuki Akiyama, Hirotaka Hachiya, Masashi Sugiya...
IJCAI
2001
14 years 11 months ago
Symbolic Dynamic Programming for First-Order MDPs
We present a dynamic programming approach for the solution of first-order Markov decisions processes. This technique uses an MDP whose dynamics is represented in a variant of the ...
Craig Boutilier, Raymond Reiter, Bob Price
ATAL
2007
Springer
15 years 4 months ago
On opportunistic techniques for solving decentralized Markov decision processes with temporal constraints
Decentralized Markov Decision Processes (DEC-MDPs) are a popular model of agent-coordination problems in domains with uncertainty and time constraints but very difficult to solve...
Janusz Marecki, Milind Tambe
CAV
2007
Springer
112views Hardware» more  CAV 2007»
15 years 4 months ago
Magnifying-Lens Abstraction for Markov Decision Processes
ng-Lens Abstraction for Markov Decision Processes⋆ In Proc. of CAV 2007: 19th International Conference on Computer-Aided Verification, Lectures Notes in Computer Science. c Spri...
Luca de Alfaro, Pritam Roy