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AAAI
2012
11 years 10 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
EOR
2006
66views more  EOR 2006»
13 years 7 months ago
Performance prediction of an unmanned airborne vehicle multi-agent system
Consider unmanned airborne vehicle (UAV) control agents in a dynamic multi-agent system. The agents must have a set of goals such as destination airport and intermediate positions...
Zhaotong Lian, Abhijit Deshmukh
ATAL
2007
Springer
14 years 1 months ago
Combinatorial resource scheduling for multiagent MDPs
Optimal resource scheduling in multiagent systems is a computationally challenging task, particularly when the values of resources are not additive. We consider the combinatorial ...
Dmitri A. Dolgov, Michael R. James, Michael E. Sam...
GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 8 months ago
Emergent architecture in self organized swarm systems for military applications
Many sectors of the military are interested in Self-Organized (SO) systems because of their flexibility, versatility and economics. The military is researching and employing auto...
Dustin J. Nowak, Gary B. Lamont, Gilbert L. Peters...
ATAL
2010
Springer
13 years 8 months ago
Self-organization for coordinating decentralized reinforcement learning
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah