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» Mean-Variance Optimization in Markov Decision Processes
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ICC
2007
IEEE
137views Communications» more  ICC 2007»
14 years 1 months ago
Optimality and Complexity of Opportunistic Spectrum Access: A Truncated Markov Decision Process Formulation
— We consider opportunistic spectrum access (OSA) which allows secondary users to identify and exploit instantaneous spectrum opportunities resulting from the bursty traffic of ...
Dejan V. Djonin, Qing Zhao, Vikram Krishnamurthy
STACS
2007
Springer
14 years 1 months ago
Pure Stationary Optimal Strategies in Markov Decision Processes
Markov decision processes (MDPs) are controllable discrete event systems with stochastic transitions. Performances of an MDP are evaluated by a payoff function. The controller of ...
Hugo Gimbert
AIPS
2004
13 years 9 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
ML
2002
ACM
143views Machine Learning» more  ML 2002»
13 years 7 months 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
AMAI
2004
Springer
14 years 1 months ago
Approximate Probabilistic Constraints and Risk-Sensitive Optimization Criteria in Markov Decision Processes
The majority of the work in the area of Markov decision processes has focused on expected values of rewards in the objective function and expected costs in the constraints. Althou...
Dmitri A. Dolgov, Edmund H. Durfee