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» Q-Decomposition for Reinforcement Learning Agents
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ATAL
2007
Springer
14 years 1 months ago
Transfer via inter-task mappings in policy search reinforcement learning
The ambitious goal of transfer learning is to accelerate learning on a target task after training on a different, but related, source task. While many past transfer methods have f...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
AAAI
2012
11 years 10 months ago
Competing with Humans at Fantasy Football: Team Formation in Large Partially-Observable Domains
We present the first real-world benchmark for sequentiallyoptimal team formation, working within the framework of a class of online football prediction games known as Fantasy Foo...
Tim Matthews, Sarvapali D. Ramchurn, Georgios Chal...
AAAI
2010
13 years 9 months ago
Learning Simulation Control in General Game-Playing Agents
The aim of General Game Playing (GGP) is to create intelligent agents that can automatically learn how to play many different games at an expert level without any human interventi...
Hilmar Finnsson, Yngvi Björnsson
IJCNN
2006
IEEE
14 years 1 months ago
Training Coordination Proxy Agents
— Delegating the coordination role to proxy agents can improve the overall outcome of the task at the expense of cognitive overload due to switching subtasks. Stability and commi...
Myriam Abramson, William Chao, Ranjeev Mittu
ATAL
2009
Springer
13 years 5 months ago
Decentralized Learning in Wireless Sensor Networks
In this paper we use a reinforcement learning algorithm with the aim to increase the autonomous lifetime of a Wireless Sensor Network (WSN) and decrease latency in a decentralized...
Mihail Mihaylov, Karl Tuyls, Ann Nowé