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ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
15 years 4 months ago
Variable resolution decomposition for robotic navigation under a POMDP framework
— Partially Observable Markov Decision Processes (POMDPs) offer a powerful mathematical framework for making optimal action choices in noisy and/or uncertain environments, in par...
Robert Kaplow, Amin Atrash, Joelle Pineau
ATAL
2009
Springer
16 years 9 days ago
Lossless clustering of histories in decentralized POMDPs
Decentralized partially observable Markov decision processes (Dec-POMDPs) constitute a generic and expressive framework for multiagent planning under uncertainty. However, plannin...
Frans A. Oliehoek, Shimon Whiteson, Matthijs T. J....
ATAL
2010
Springer
15 years 6 months ago
Point-based backup for decentralized POMDPs: complexity and new algorithms
Decentralized POMDPs provide an expressive framework for sequential multi-agent decision making. Despite their high complexity, there has been significant progress in scaling up e...
Akshat Kumar, Shlomo Zilberstein
ATAL
2007
Springer
15 years 12 months ago
Q-value functions for decentralized POMDPs
Planning in single-agent models like MDPs and POMDPs can be carried out by resorting to Q-value functions: a (near-) optimal Q-value function is computed in a recursive manner by ...
Frans A. Oliehoek, Nikos A. Vlassis
ECML
2005
Springer
15 years 11 months ago
Active Learning in Partially Observable Markov Decision Processes
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
Robin Jaulmes, Joelle Pineau, Doina Precup