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Coevolutive planning in markov decision processes
Proceedings of the first international joint conference on Autonomous agents and multiagent systems part 2 - AAMAS '02, 2002We investigate the idea of having groups of agents coevolving in order to iteratively refine multi-agent plans. This idea we called coevolution is formalized and analyzed in a general purpose and applied to the stochastic control frameworks that use an explicit model of the world\,: coevolution can directly be adapted to the frameworks of Multi-Agent ...
Scherrer, Bruno, Charpillet, François
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IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2013
Greenhouse gas emissions and global warming have become vital problems to human society. About 40% of the carbon dioxide is emitted from electric power generation in the United States. Due to the lack of consideration in the system design and the lack of
Lin Li, Zeyi Sun
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Greenhouse gas emissions and global warming have become vital problems to human society. About 40% of the carbon dioxide is emitted from electric power generation in the United States. Due to the lack of consideration in the system design and the lack of
Lin Li, Zeyi Sun
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On the Generation of Markov Decision Processes
Journal of the Operational Research Society, 1995Comparisons of the performance of solution algorithms for Markov decision processes rely heavily on problem generators to provide sizeable sets of test problems. Existing generation techniques allow little control over the properties of the test problems and often result in problems which are not typical of real-world examples.
Lyn C. Thomas +2 more
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Adaptive policies for real-time video transmission: A Markov decision process framework
2011 18th IEEE International Conference on Image Processing, 2011We study the problem of adaptive video data scheduling over wireless channels. We prove that, under certain assumptions, adaptive video scheduling can be reduced to a Markov decision process over a finite state space. Therefore, the scheduling policy can
Chao Chen +3 more
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IEEE Transactions on Power Systems, 2010
We develop models and the associated solution tools for devising optimal maintenance strategies, helping reduce the operation costs, and enhancing the marketability of wind power.
E. Byon, Yu Ding
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We develop models and the associated solution tools for devising optimal maintenance strategies, helping reduce the operation costs, and enhancing the marketability of wind power.
E. Byon, Yu Ding
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2007
In Chapter 2, we introduced the basic principles of PA and derived the performance derivative formulas for queueing networks and Markov and semi-Markov systems with these principles. In Chapter 3, we developed sample-path-based (on-line learning) algorithms for estimating the performance derivatives and sample-path-based optimization schemes.
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In Chapter 2, we introduced the basic principles of PA and derived the performance derivative formulas for queueing networks and Markov and semi-Markov systems with these principles. In Chapter 3, we developed sample-path-based (on-line learning) algorithms for estimating the performance derivatives and sample-path-based optimization schemes.
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2019
This chapter considers the problem of minimizing the expectation of a reward for a controlled Markov chain process, either with a finite horizon, or an infinite one for which the reward has discounted values, including the cases of exit times and stopping decisions. The value and policy (Howard) iterations are compared.
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This chapter considers the problem of minimizing the expectation of a reward for a controlled Markov chain process, either with a finite horizon, or an infinite one for which the reward has discounted values, including the cases of exit times and stopping decisions. The value and policy (Howard) iterations are compared.
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A Markov decision process approach to vacant taxi routing with e-hailing
Transportation Research Part B: Methodological, 2019Xinlian Yu +3 more
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Ordinal Decision Models for Markov Decision Processes
2012Setting the values of rewards in Markov decision processes (MDP) may be a difficult task. In this paper, we consider two ordinal decision models for MDPs where only an order is known over rewards. The first one, which has been proposed recently in MDPs [23], defines preferences with respect to a reference point.
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