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ICAC
2008
IEEE
15 years 6 months ago
Utility-Based Reinforcement Learning for Reactive Grids
—Large scale production grids are an important case for autonomic computing. They follow a mutualization paradigm: decision-making (human or automatic) is distributed and largely...
Julien Perez, Cécile Germain-Renaud, Bal&aa...
ICRA
2008
IEEE
128views Robotics» more  ICRA 2008»
15 years 6 months ago
Learning from human teachers with Socially Guided Exploration
— We present a learning mechanism, Socially Guided Exploration, in which a robot learns new tasks through a combination of self-exploration and social interaction. The system’s...
Cynthia Breazeal, Andrea Lockerd Thomaz
JAIR
2000
131views more  JAIR 2000»
14 years 11 months ago
An Application of Reinforcement Learning to Dialogue Strategy Selection in a Spoken Dialogue System for Email
This paper describes a novel method by which a spoken dialogue system can learn to choose an optimal dialogue strategy from its experience interacting with human users. The method...
Marilyn A. Walker
ML
2002
ACM
114views Machine Learning» more  ML 2002»
14 years 11 months ago
Building a Basic Block Instruction Scheduler with Reinforcement Learning and Rollouts
The execution order of a block of computer instructions on a pipelined machine can make a difference in running time by a factor of two or more. Compilers use heuristic schedulers...
Amy McGovern, J. Eliot B. Moss, Andrew G. Barto
NIPS
1996
15 years 1 months ago
Reinforcement Learning for Mixed Open-loop and Closed-loop Control
Closed-loop control relies on sensory feedback that is usually assumed to be free. But if sensing incurs a cost, it may be coste ective to take sequences of actions in open-loop m...
Eric A. Hansen, Andrew G. Barto, Shlomo Zilberstei...