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ICML
2010
IEEE
13 years 5 months ago
Constructing States for Reinforcement Learning
POMDPs are the models of choice for reinforcement learning (RL) tasks where the environment cannot be observed directly. In many applications we need to learn the POMDP structure ...
M. M. Hassan Mahmud
ICRA
2010
IEEE
117views Robotics» more  ICRA 2010»
13 years 5 months ago
Learning reliable and efficient navigation with a humanoid
Reliable and efficient navigation with a humanoid robot is a difficult task. First, the motion commands are executed rather inaccurately due to backlash in the joints or foot slipp...
Stefan Oßwald, Armin Hornung, Maren Bennewit...
TCSV
2008
175views more  TCSV 2008»
13 years 7 months ago
Expandable Data-Driven Graphical Modeling of Human Actions Based on Salient Postures
This paper presents a graphical model for learning and recognizing human actions. Specifically, we propose to encode actions in a weighted directed graph, referred to as action gra...
Wanqing Li, Zhengyou Zhang, Zicheng Liu
NIPS
1993
13 years 9 months ago
Robust Reinforcement Learning in Motion Planning
While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
NIPS
2007
13 years 9 months ago
Bayes-Adaptive POMDPs
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...