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148
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ICTAI
2010
IEEE
15 years 1 months ago
A Closer Look at MOMDPs
Abstract--The difficulties encountered in sequential decisionmaking problems under uncertainty are often linked to the large size of the state space. Exploiting the structure of th...
Mauricio Araya-López, Vincent Thomas, Olivi...
139
Voted
ATAL
2006
Springer
15 years 7 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....
139
Voted
AAAI
2007
15 years 6 months ago
Scaling Up: Solving POMDPs through Value Based Clustering
Partially Observable Markov Decision Processes (POMDPs) provide an appropriately rich model for agents operating under partial knowledge of the environment. Since finding an opti...
Yan Virin, Guy Shani, Solomon Eyal Shimony, Ronen ...
143
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IJCAI
2003
15 years 5 months ago
Taming Decentralized POMDPs: Towards Efficient Policy Computation for Multiagent Settings
The problem of deriving joint policies for a group of agents that maximize some joint reward function can be modeled as a decentralized partially observable Markov decision proces...
Ranjit Nair, Milind Tambe, Makoto Yokoo, David V. ...
178
Voted
AI
2011
Springer
14 years 7 months ago
Decentralized MDPs with sparse interactions
In this work, we explore how local interactions can simplify the process of decision-making in multiagent systems, particularly in multirobot problems. We review a recent decision-...
Francisco S. Melo, Manuela M. Veloso