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» A social reinforcement learning agent
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IWANN
1999
Springer
14 years 2 months ago
Using Temporal Neighborhoods to Adapt Function Approximators in Reinforcement Learning
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
R. Matthew Kretchmar, Charles W. Anderson
AIED
2007
Springer
14 years 4 months ago
MathGirls: Toward Developing Girls' Positive Attitude and Self-Efficacy through Pedagogical Agents
MathGirls is a pedagogical-agent-based environment designed for high-school girls learning introductory algebra. Since females are in general more interested in interactive computi...
Yanghee Kim, Quan Wei, Beijie Xu, Youngah Ko, Vess...
JMLR
2006
153views more  JMLR 2006»
13 years 9 months ago
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
Jelle R. Kok, Nikos A. Vlassis
MAGS
2010
81views more  MAGS 2010»
13 years 4 months ago
Task allocation learning in a multiagent environment: Application to the RoboCupRescue simulation
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, Patric...
ICES
2003
Springer
125views Hardware» more  ICES 2003»
14 years 3 months ago
Evolving Reinforcement Learning-Like Abilities for Robots
Abstract. In [8] Yamauchi and Beer explored the abilities of continuous time recurrent neural networks (CTRNNs) to display reinforcementlearning like abilities. The investigated ta...
Jesper Blynel