Sciweavers

2108 search results - page 31 / 422
» Tracking in Reinforcement Learning
Sort
View
IJCAI
2007
13 years 8 months ago
Bayesian Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
Deepak Ramachandran, Eyal Amir
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
13 years 6 months ago
Generalized model learning for Reinforcement Learning on a humanoid robot
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...
Todd Hester, Michael Quinlan, Peter Stone
IJCAI
2003
13 years 8 months ago
Covariant Policy Search
We investigate the problem of non-covariant behavior of policy gradient reinforcement learning algorithms. The policy gradient approach is amenable to analysis by information geom...
J. Andrew Bagnell, Jeff G. Schneider
AAAI
2010
13 years 8 months ago
Bayesian Policy Search for Multi-Agent Role Discovery
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
Aaron Wilson, Alan Fern, Prasad Tadepalli
ATAL
2010
Springer
13 years 8 months ago
Combining manual feedback with subsequent MDP reward signals for reinforcement learning
As learning agents move from research labs to the real world, it is increasingly important that human users, including those without programming skills, be able to teach agents de...
W. Bradley Knox, Peter Stone