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174
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ATAL
2009
Springer
16 years 1 months ago
2009
Springer
One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
170
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ATAL
2009
Springer
16 years 1 months ago
2009
Springer
In large systems, it is important for agents to learn to act effectively, but sophisticated multi-agent learning algorithms generally do not scale. An alternative approach is to ...
150
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ATAL
2009
Springer
16 years 1 months ago
2009
Springer
Self-organising multi-agent systems provide a suitable paradigm for developing autonomic computing systems that manage themselves. Towards this goal, we demonstrate a robust, dece...
196
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ATAL
2009
Springer
16 years 1 months ago
2009
Springer
Computational trust and reputation models have been recognized as one of the key technologies required to design and implement agent systems. These models manage and aggregate the...
216
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ESAW
2009
Springer
16 years 1 months ago
2009
Springer
Abstract. Load-Balancing is a significant problem in heterogeneous distributed systems. There exist many load balancing algorithms, however, most approaches are very problem speci...