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IJCAI
2003
13 years 7 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. ...
AAAI
2006
13 years 7 months ago
Compact, Convex Upper Bound Iteration for Approximate POMDP Planning
Partially observable Markov decision processes (POMDPs) are an intuitive and general way to model sequential decision making problems under uncertainty. Unfortunately, even approx...
Tao Wang, Pascal Poupart, Michael H. Bowling, Dale...
UAI
2004
13 years 7 months ago
Discretized Approximations for POMDP with Average Cost
In this paper, we propose a new lower approximation scheme for POMDP with discounted and average cost criterion. The approximating functions are determined by their values at a fi...
Huizhen Yu, Dimitri P. Bertsekas
ATAL
2006
Springer
13 years 9 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....
AAAI
2008
13 years 8 months ago
Generalized Point Based Value Iteration for Interactive POMDPs
We develop a point based method for solving finitely nested interactive POMDPs approximately. Analogously to point based value iteration (PBVI) in POMDPs, we maintain a set of bel...
Prashant Doshi, Dennis Perez