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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
15 years 4 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
ATAL
2006
Springer
15 years 10 months ago
Learning against multiple opponents
We address the problem of learning in repeated N-player (as opposed to 2-player) general-sum games. We describe an extension to existing criteria focusing explicitly on such setti...
Thuc Vu, Rob Powers, Yoav Shoham
TSMC
1998
78views more  TSMC 1998»
15 years 5 months ago
Automata learning and intelligent tertiary searching for stochastic point location
—Consider the problem of a robot (learning mechanism or algorithm) attempting to locate a point on a line. The mechanism interacts with a random environment which essentially inf...
B. John Oommen, Govindachari Raghunath
CEC
2010
IEEE
15 years 6 months ago
Coevolutionary Temporal Difference Learning for small-board Go
—In this paper we apply Coevolutionary Temporal Difference Learning (CTDL), a hybrid of coevolutionary search and reinforcement learning proposed in our former study, to evolve s...
Krzysztof Krawiec, Marcin Szubert
ICCV
2003
IEEE
16 years 8 months ago
Automatically Labeling Video Data Using Multi-class Active Learning
Labeling video data is an essential prerequisite for many vision applications that depend on training data, such as visual information retrieval, object recognition, and human act...
Rong Yan, Jie Yang, Alexander G. Hauptmann