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» Application of reinforcement learning to the game of Othello
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NIPS
1996
13 years 6 months ago
Why did TD-Gammon Work?
Although TD-Gammon is one of the major successes in machine learning, it has not led to similar impressive breakthroughs in temporal difference learning for other applications or ...
Jordan B. Pollack, Alan D. Blair
EWCBR
2008
Springer
13 years 7 months ago
Forgetting Reinforced Cases
To meet time constraints, a CBR system must control the time spent searching in the case base for a solution. In this paper, we presents the results of a case study comparing the p...
Houcine Romdhane, Luc Lamontagne
PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
13 years 10 months ago
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
Philippe Rolet, Michèle Sebag, Olivier Teyt...
ROMAN
2007
IEEE
150views Robotics» more  ROMAN 2007»
13 years 11 months ago
Asymmetric Interpretations of Positive and Negative Human Feedback for a Social Learning Agent
— The ability for people to interact with robots and teach them new skills will be crucial to the successful application of robots in everyday human environments. In order to des...
Andrea Lockerd Thomaz, Cynthia Breazeal
ECAI
2000
Springer
13 years 9 months ago
Learning to Use Operational Advice
We address the problem of advice-taking in a given domain, in particular for building a game-playing program. Our approach to solving it strives for the application of machine lea...
Johannes Fürnkranz, Bernhard Pfahringer, Herm...