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AAAI
2010
15 years 7 months ago
Reinforcement Learning Via Practice and Critique Advice
We consider the problem of incorporating end-user advice into reinforcement learning (RL). In our setting, the learner alternates between practicing, where learning is based on ac...
Kshitij Judah, Saikat Roy, Alan Fern, Thomas G. Di...
CVPR
2011
IEEE
15 years 2 months ago
Shape Grammar Parsing via Reinforcement Learning
This paper tackles shape grammar parsing for facade segmentation using a novel optimization approach based on reinforcement learning (RL). To this end, we use a binary recursive g...
Olivier Teboul, Iasonas Kokkinos, Panagiotis Kouts...
ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
16 years 15 days 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...
AIMSA
2004
Springer
15 years 9 months ago
Towards Well-Defined Multi-agent Reinforcement Learning
Multi-agent reinforcement learning (MARL) is an emerging area of research. However, it lacks two important elements: a coherent view on MARL, and a well-defined problem objective. ...
Rinat Khoussainov
JMLR
2010
125views more  JMLR 2010»
15 years 26 days ago
Variational methods for Reinforcement Learning
We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
Thomas Furmston, David Barber