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» How to Dynamically Merge Markov Decision Processes
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105
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ML
2002
ACM
143views Machine Learning» more  ML 2002»
15 years 6 days ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
98
Voted
ATAL
2004
Springer
15 years 6 months ago
Decentralized Markov Decision Processes with Event-Driven Interactions
Decentralized MDPs provide a powerful formal framework for planning in multi-agent systems, but the complexity of the model limits its usefulness. We study in this paper a class o...
Raphen Becker, Shlomo Zilberstein, Victor R. Lesse...
131
Voted
AIPS
2004
15 years 1 months ago
Optimal Resource Allocation and Policy Formulation in Loosely-Coupled Markov Decision Processes
The problem of optimal policy formulation for teams of resource-limited agents in stochastic environments is composed of two strongly-coupled subproblems: a resource allocation pr...
Dmitri A. Dolgov, Edmund H. Durfee
93
Voted
UAI
2004
15 years 1 months ago
Dynamic Programming for Structured Continuous Markov Decision Problems
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamica...
Zhengzhu Feng, Richard Dearden, Nicolas Meuleau, R...
DAC
2000
ACM
16 years 1 months ago
Dynamic power management of complex systems using generalized stochastic Petri nets
In this paper, we introduce a new technique for modeling and solving the dynamic power management (DPM) problem for systems with complex behavioral characteristics such as concurr...
Qinru Qiu, Qing Wu, Massoud Pedram