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ICML
2006
IEEE
15 years 10 months ago
PAC model-free reinforcement learning
For a Markov Decision Process with finite state (size S) and action spaces (size A per state), we propose a new algorithm--Delayed Q-Learning. We prove it is PAC, achieving near o...
Alexander L. Strehl, Lihong Li, Eric Wiewiora, Joh...
IROS
2007
IEEE
144views Robotics» more  IROS 2007»
15 years 4 months ago
Global action selection for illumination invariant color modeling
— A major challenge in the path of widespread use of mobile robots is the ability to function autonomously, learning useful features from the environment and using them to adapt ...
Mohan Sridharan, Peter Stone
ISWC
2006
IEEE
15 years 3 months ago
Discovering Characteristic Actions from On-Body Sensor Data
We present an approach to activity discovery, the unsupervised identification and modeling of human actions embedded in a larger sensor stream. Activity discovery can be seen as ...
David Minnen, Thad Starner, Irfan A. Essa, Charles...
ACCV
2010
Springer
14 years 4 months ago
Affordance Mining: Forming Perception through Action
This work employs data mining algorithms to discover visual entities that are strongly associated to autonomously discovered modes of action, in an embodied agent. Mappings are lea...
Liam Ellis, Michael Felsberg, Richard Bowden
AAAI
1997
14 years 11 months ago
Reinforcement Learning with Time
This paper steps back from the standard infinite horizon formulation of reinforcement learning problems to consider the simpler case of finite horizon problems. Although finite ho...
Daishi Harada