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GECCO
2006
Springer
13 years 8 months ago
2006
Springer
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
GECCO
2006
Springer
13 years 8 months ago
2006
Springer
In this paper we propose a Bayesian framework for XCS [9], called BXCS. Following [4], we use probability distributions to represent the uncertainty over the classifier estimates ...
ISLPED
2003
ACM
13 years 10 months ago
2003
ACM
Energy constrained systems such as sensor networks can increase their usable lifetimes by extracting energy from their environment. However, environmental energy will typically no...
OSDI
1996
ACM
13 years 6 months ago
1996
ACM
Traditional processor scheduling mechanisms in operating systems are fairly rigid, often supportingonly one fixed scheduling policy, or, at most, a few "scheduling classes&qu...
ATAL
2004
Springer
13 years 10 months ago
2004
Springer
This paper investigates a relatively new direction in Multiagent Reinforcement Learning. Most multiagent learning techniques focus on Nash equilibria as elements of both the learn...