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ATAL
2007
Springer
15 years 10 months 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
CACM
2000
147views more  CACM 2000»
15 years 3 months ago
Adaptive Web sites
Today's Web sites are intricate but not intelligent; while Web navigation is dynamic and idiosyncratic, all too often Web sites are fossils cast in HTML. In response, this pa...
Mike Perkowitz, Oren Etzioni
MICAI
2010
Springer
15 years 2 months ago
Teaching a Robot to Perform Tasks with Voice Commands
The full deployment of service robots in daily activities will require the robot to adapt to the needs of non-expert users, particularly, to learn how to perform new tasks from “...
Ana C. Tenorio-Gonzalez, Eduardo F. Morales, Luis ...
ALT
2005
Springer
16 years 23 days ago
Defensive Universal Learning with Experts
This paper shows how universal learning can be achieved with expert advice. To this aim, we specify an experts algorithm with the following characteristics: (a) it uses only feedba...
Jan Poland, Marcus Hutter
AGENTS
2001
Springer
15 years 8 months ago
A social reinforcement learning agent
We report on the use of reinforcement learning with Cobot, a software agent residing in the wellknown online community LambdaMOO. Our initial work on Cobot (Isbell et al.2000) pro...
Charles Lee Isbell Jr., Christian R. Shelton, Mich...