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121
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ECAI
2004
Springer
15 years 6 months ago
On-Line Search for Solving Markov Decision Processes via Heuristic Sampling
In the past, Markov Decision Processes (MDPs) have become a standard for solving problems of sequential decision under uncertainty. The usual request in this framework is the compu...
Laurent Péret, Frédérick Garc...
113
Voted
JAIR
2000
152views more  JAIR 2000»
15 years 28 days ago
Value-Function Approximations for Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Milos Hauskrecht
105
Voted
ATAL
2009
Springer
15 years 7 months ago
Point-based incremental pruning heuristic for solving finite-horizon DEC-POMDPs
Recent scaling up of decentralized partially observable Markov decision process (DEC-POMDP) solvers towards realistic applications is mainly due to approximate methods. Of this fa...
Jilles Steeve Dibangoye, Abdel-Illah Mouaddib, Bra...
107
Voted
AIPS
2000
15 years 2 months ago
On-line Scheduling via Sampling
1 We consider the problem of scheduling an unknown sequence of tasks for a single server as the tasks arrive with the goal off maximizing the total weighted value of the tasks serv...
Hyeong Soo Chang, Robert Givan, Edwin K. P. Chong
106
Voted
JAIR
2006
120views more  JAIR 2006»
15 years 1 months ago
FluCaP: A Heuristic Search Planner for First-Order MDPs
We present a heuristic search algorithm for solving first-order Markov Decision Processes (FOMDPs). Our approach combines first-order state abstraction that avoids evaluating stat...
Steffen Hölldobler, Eldar Karabaev, Olga Skvo...