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AR
2007
105views more  AR 2007»
15 years 4 months ago
Reinforcement learning of a continuous motor sequence with hidden states
—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
Hiroaki Arie, Tetsuya Ogata, Jun Tani, Shigeki Sug...
JAIR
2000
131views more  JAIR 2000»
15 years 3 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
GECCO
2011
Springer
276views Optimization» more  GECCO 2011»
14 years 7 months ago
Evolution of reward functions for reinforcement learning
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...
Scott Niekum, Lee Spector, Andrew G. Barto
SIGUCCS
2000
ACM
15 years 8 months ago
Training... A Key to Better Help Desk Consultants
The quality of student consultants and their development through training and education are major factors in determining long-term effectiveness of university Help Desk. To hire a...
Anna Maria Perez, Andrea J. Moore
FLAIRS
2006
15 years 5 months ago
Using Active Relocation to Aid Reinforcement Learning
We propose a new framework for aiding a reinforcement learner by allowing it to relocate, or move, to a state it selects so as to decrease the number of steps it needs to take in ...
Lilyana Mihalkova, Raymond J. Mooney