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» Reinforcement Learning: An Introduction
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ATAL
2004
Springer
14 years 1 months ago
When to Apply the Fifth Commandment: The Effects of Parenting on Genetic and Learning Agents
This paper explores hybrid agents that use a variety of techniques to improve their performance in an environment over time. We considered, specifically, geneticlearning-parentin...
Michael Berger, Jeffrey S. Rosenschein
ESANN
2007
13 years 9 months ago
Applying the Episodic Natural Actor-Critic Architecture to Motor Primitive Learning
In this paper, we investigate motor primitive learning with the Natural Actor-Critic approach. The Natural Actor-Critic consists out of actor updates which are achieved using natur...
Jan Peters, Stefan Schaal
ML
1998
ACM
136views Machine Learning» more  ML 1998»
13 years 8 months ago
Co-Evolution in the Successful Learning of Backgammon Strategy
Following Tesauro’s work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of t...
Jordan B. Pollack, Alan D. Blair
MAGS
2010
81views more  MAGS 2010»
13 years 3 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...
ICML
2002
IEEE
14 years 9 months ago
Learning from Scarce Experience
Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...
Leonid Peshkin, Christian R. Shelton