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» Exploiting Myopic Learning
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ICML
2005
IEEE
14 years 6 months ago
Learning to compete, compromise, and cooperate in repeated general-sum games
Learning algorithms often obtain relatively low average payoffs in repeated general-sum games between other learning agents due to a focus on myopic best-response and one-shot Nas...
Jacob W. Crandall, Michael A. Goodrich
AAAI
1998
13 years 6 months ago
Bayesian Q-Learning
A central problem in learning in complex environmentsis balancing exploration of untested actions against exploitation of actions that are known to be good. The benefit of explora...
Richard Dearden, Nir Friedman, Stuart J. Russell
CVPR
2010
IEEE
14 years 1 months ago
Far-Sighted Active Learning on a Budget for Image and Video Recognition
Active learning methods aim to select the most informative unlabeled instances to label first, and can help to focus image or video annotations on the examples that will most impr...
Sudheendra Vijayanarasimhan, Prateek Jain, Kristen...
IJCAI
2007
13 years 6 months ago
A Decision-Theoretic Model of Assistance
There is a growing interest in intelligent assistants for a variety of applications from organizing tasks for knowledge workers to helping people with dementia. In this paper, we ...
Alan Fern, Sriraam Natarajan, Kshitij Judah, Prasa...
CORR
2002
Springer
108views Education» more  CORR 2002»
13 years 5 months ago
Learning to Play Games in Extensive Form by Valuation
Game theoretic models of learning which are based on the strategic form of the game cannot explain learning in games with large extensive form. We study learning in such games by ...
Philippe Jehiel, Dov Samet