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» Tracking in Reinforcement Learning
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ATAL
2009
Springer
15 years 4 months ago
Learning of coordination: exploiting sparse interactions in multiagent systems
Creating coordinated multiagent policies in environments with uncertainty is a challenging problem, which can be greatly simplified if the coordination needs are known to be limi...
Francisco S. Melo, Manuela M. Veloso
CEC
2005
IEEE
14 years 12 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...
ICML
2006
IEEE
15 years 10 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
AAAI
1996
14 years 11 months ago
Evolution-Based Discovery of Hierarchical Behaviors
Procedural representations of control policies have two advantages when facing the scale-up problem in learning tasks. First they are implicit, with potential for inductive genera...
Justinian P. Rosca, Dana H. Ballard
ICML
2004
IEEE
15 years 10 months ago
Learning to track 3D human motion from silhouettes
Ankur Agarwal, Bill Triggs