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» Algorithm Selection using Reinforcement Learning
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AIIA
2007
Springer
15 years 8 months ago
Reinforcement Learning in Complex Environments Through Multiple Adaptive Partitions
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
Andrea Bonarini, Alessandro Lazaric, Marcello Rest...
ML
2000
ACM
150views Machine Learning» more  ML 2000»
15 years 2 months ago
Adaptive Retrieval Agents: Internalizing Local Context and Scaling up to the Web
This paper discusses a novel distributed adaptive algorithm and representation used to construct populations of adaptive Web agents. These InfoSpiders browse networked information ...
Filippo Menczer, Richard K. Belew
ATAL
2006
Springer
15 years 6 months ago
Learning the required number of agents for complex tasks
Coordinating agents in a complex environment is a hard problem, but it can become even harder when certain characteristics of the tasks, like the required number of agents, are un...
Sébastien Paquet, Brahim Chaib-draa
COLT
2004
Springer
15 years 7 months ago
Reinforcement Learning for Average Reward Zero-Sum Games
Abstract. We consider Reinforcement Learning for average reward zerosum stochastic games. We present and analyze two algorithms. The first is based on relative Q-learning and the ...
Shie Mannor
ECAI
2010
Springer
15 years 3 months ago
The Dynamics of Multi-Agent Reinforcement Learning
Abstract. Infinite-horizon multi-agent control processes with nondeterminism and partial state knowledge have particularly interesting properties with respect to adaptive control, ...
Luke Dickens, Krysia Broda, Alessandra Russo