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» Coordinated Reinforcement Learning
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130
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GECCO
2006
Springer
175views Optimization» more  GECCO 2006»
15 years 7 months ago
A computational theory of adaptive behavior based on an evolutionary reinforcement mechanism
Two mathematical and two computational theories from the field of human and animal learning are combined to produce a more general theory of adaptive behavior. The cornerstone of ...
J. J. McDowell, Paul L. Soto, Jesse Dallery, Saule...
NN
2006
Springer
15 years 3 months ago
Neural systems implicated in delayed and probabilistic reinforcement
This review considers the theoretical problems facing agents that must learn and choose on the basis of reward or reinforcement that is uncertain or delayed, in implicit or proced...
Rudolf N. Cardinal
ICML
2005
IEEE
16 years 4 months ago
Interactive learning of mappings from visual percepts to actions
We introduce flexible algorithms that can automatically learn mappings from images to actions by interacting with their environment. They work by introducing an image classifier i...
Justus H. Piater, Sébastien Jodogne
156
Voted
CEC
2005
IEEE
15 years 5 months ago
XCS with computed prediction in continuous multistep environments
We apply XCS with computed prediction (XCSF) to tackle multistep reinforcement learning problems involving continuous inputs. In essence we use XCSF as a method of generalized rein...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
118
Voted
ICML
2006
IEEE
16 years 4 months ago
An intrinsic reward mechanism for efficient exploration
How should a reinforcement learning agent act if its sole purpose is to efficiently learn an optimal policy for later use? In other words, how should it explore, to be able to exp...
Özgür Simsek, Andrew G. Barto