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» Reinforcement Learning in MirrorBot
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NN
2006
Springer
15 years 1 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
IAT
2003
IEEE
15 years 6 months ago
Asymmetric Multiagent Reinforcement Learning
A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the ...
Ville Könönen
CEC
2005
IEEE
15 years 3 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...
AAAI
1996
15 years 2 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
SOCROB
2010
126views Robotics» more  SOCROB 2010»
14 years 12 months ago
Using the Interaction Rhythm as a Natural Reinforcement Signal for Social Robots: A Matter of Belief
Abstract. In this paper, we present the results of a pilot study of a human robot interaction experiment where the rhythm of the interaction is used as a reinforcement signal to le...
Antoine Hiolle, Lola Cañamero, Pierre Andry...