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ATAL
2007
Springer
16 years 20 days ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
AGENTS
1999
Springer
15 years 10 months ago
A Personal News Agent That Talks, Learns and Explains
Most work on intelligent information agents has thus far focused on systems that are accessible through the World Wide Web. As demanding schedules prohibit people from continuous ...
Daniel Billsus, Michael J. Pazzani
AROBOTS
2007
159views more  AROBOTS 2007»
15 years 6 months ago
Structure-based color learning on a mobile robot under changing illumination
— A central goal of robotics and AI is to be able to deploy an agent to act autonomously in the real world over an extended period of time. To operate in the real world, autonomo...
Mohan Sridharan, Peter Stone
ICRA
2010
IEEE
158views Robotics» more  ICRA 2010»
15 years 5 months ago
Movement templates for learning of hitting and batting
Abstract— Hitting and batting tasks, such as tennis forehands, ping-pong strokes, or baseball batting, depend on predictions where the ball can be intercepted and how it can prop...
Jens Kober, Katharina Mülling, Oliver Kroemer...
IJRR
2011
159views more  IJRR 2011»
15 years 1 months ago
Learning visual representations for perception-action systems
We discuss vision as a sensory modality for systems that effect actions in response to perceptions. While the internal representations informed by vision may be arbitrarily compl...
Justus H. Piater, Sébastien Jodogne, Renaud...