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FLAIRS
1998
14 years 11 months ago
Analytical Design of Reinforcement Learning Tasks
Reinforcement learning (RL) problems constitute an important class of learning and control problems faced by artificial intelligence systems. In these problems, one is faced with ...
Robert E. Smith
ICML
1995
IEEE
15 years 11 months ago
Ant-Q: A Reinforcement Learning Approach to the Traveling Salesman Problem
In this paper we introduce Ant-Q, a family of algorithms which present many similarities with Q-learning (Watkins, 1989), and which we apply to the solution of symmetric and asymm...
Luca Maria Gambardella, Marco Dorigo
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
14 years 7 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
IROS
2007
IEEE
144views Robotics» more  IROS 2007»
15 years 4 months ago
Using reinforcement learning to adapt an imitation task
Abstract— The goal of developing algorithms for programming robots by demonstration is to create an easy way of programming robots that can be accomplished by everyone. When a de...
Florent Guenter, Aude Billard
ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
15 years 4 months ago
Bayesian reinforcement learning in continuous POMDPs with application to robot navigation
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...