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ATAL
2006
Springer
13 years 8 months ago
Decentralized planning under uncertainty for teams of communicating agents
Decentralized partially observable Markov decision processes (DEC-POMDPs) form a general framework for planning for groups of cooperating agents that inhabit a stochastic and part...
Matthijs T. J. Spaan, Geoffrey J. Gordon, Nikos A....
ICRA
2007
IEEE
126views Robotics» more  ICRA 2007»
13 years 11 months ago
A formal framework for robot learning and control under model uncertainty
— While the Partially Observable Markov Decision Process (POMDP) provides a formal framework for the problem of robot control under uncertainty, it typically assumes a known and ...
Robin Jaulmes, Joelle Pineau, Doina Precup
ISIPTA
2003
IEEE
124views Mathematics» more  ISIPTA 2003»
13 years 10 months ago
Decision Making with Imprecise Second-Order Probabilities
In this paper we consider decision making under hierarchical imprecise uncertainty models and derive general algorithms to determine optimal actions. Numerical examples illustrate...
Lev V. Utkin
AIPS
2008
13 years 7 months ago
Multiagent Planning Under Uncertainty with Stochastic Communication Delays
We consider the problem of cooperative multiagent planning under uncertainty, formalized as a decentralized partially observable Markov decision process (Dec-POMDP). Unfortunately...
Matthijs T. J. Spaan, Frans A. Oliehoek, Nikos A. ...
IJCAI
2007
13 years 6 months ago
Memory-Bounded Dynamic Programming for DEC-POMDPs
Decentralized decision making under uncertainty has been shown to be intractable when each agent has different partial information about the domain. Thus, improving the applicabil...
Sven Seuken, Shlomo Zilberstein