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» Markov Decision Processes with Arbitrary Reward Processes
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CDC
2009
IEEE
169views Control Systems» more  CDC 2009»
15 years 4 months ago
Parametric regret in uncertain Markov decision processes
— We consider decision making in a Markovian setup where the reward parameters are not known in advance. Our performance criterion is the gap between the performance of the best ...
Huan Xu, Shie Mannor
AAAI
2004
15 years 1 months ago
Solving Generalized Semi-Markov Decision Processes Using Continuous Phase-Type Distributions
We introduce the generalized semi-Markov decision process (GSMDP) as an extension of continuous-time MDPs and semi-Markov decision processes (SMDPs) for modeling stochastic decisi...
Håkan L. S. Younes, Reid G. Simmons
ATAL
2007
Springer
15 years 5 months ago
On opportunistic techniques for solving decentralized Markov decision processes with temporal constraints
Decentralized Markov Decision Processes (DEC-MDPs) are a popular model of agent-coordination problems in domains with uncertainty and time constraints but very difficult to solve...
Janusz Marecki, Milind Tambe
WINET
2010
127views more  WINET 2010»
14 years 10 months ago
A Markov Decision Process based flow assignment framework for heterogeneous network access
We consider a scenario where devices with multiple networking capabilities access networks with heterogeneous characteristics. In such a setting, we address the problem of effici...
Jatinder Pal Singh, Tansu Alpcan, Piyush Agrawal, ...
SARA
2007
Springer
15 years 5 months ago
Active Learning of Dynamic Bayesian Networks in Markov Decision Processes
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
Anders Jonsson, Andrew G. Barto