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» Efficient Approximation of Optimal Control for Markov Games
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103
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ATAL
2005
Springer
15 years 3 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
ATAL
2003
Springer
15 years 2 months ago
Optimizing information exchange in cooperative multi-agent systems
Decentralized control of a cooperative multi-agent system is the problem faced by multiple decision-makers that share a common set of objectives. The decision-makers may be robots...
Claudia V. Goldman, Shlomo Zilberstein
AAAI
2000
14 years 10 months ago
Back to the Future for Consistency-Based Trajectory Tracking
Given a model of a physical process and a sequence of commands and observations received over time, the task of an autonomous controller is to determine the likely states of the p...
James Kurien, P. Pandurang Nayak
PUK
2000
14 years 10 months ago
Dynamic Scheduling of Progressive Processing Plans
Progressive processing plans allow systems to tradeoff computational resources against the quality of service by specifying alternative ways in which to accomplish each step. When ...
Shlomo Zilberstein, Abdel-Illah Mouaddib, Andrew A...
93
Voted
AAAI
2012
12 years 12 months ago
Kernel-Based Reinforcement Learning on Representative States
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Branislav Kveton, Georgios Theocharous