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ECAI
2004
Springer
13 years 9 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...
JAIR
2000
152views more  JAIR 2000»
13 years 4 months 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
ATAL
2009
Springer
13 years 11 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...
AIPS
2000
13 years 5 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
JAIR
2006
120views more  JAIR 2006»
13 years 4 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...