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» Multiple Model-Based Reinforcement Learning
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SMC
2007
IEEE
118views Control Systems» more  SMC 2007»
14 years 1 months ago
One-class learning with multi-objective genetic programming
One-class classification naturally only provides one class of exemplars on which to construct the classification model. In this work, multiobjective genetic programming (GP) all...
Robert Curry, Malcolm I. Heywood

Publication
200views
12 years 3 months ago
Learning Tags from Unsegmented Videos of Multiple Human Actions
Providing methods to support semantic interaction with growing volumes of video data is an increasingly important challenge for data mining. To this end, there has been some succes...
Timothy Hospedales, Shaogang Gong, Tao Xiang
NIPS
2001
13 years 8 months ago
The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay
Tangential hand velocity profiles of rapid human arm movements often appear as sequences of several bell-shaped acceleration-deceleration phases called submovements or movement un...
Michael Kositsky, Andrew G. Barto
CI
2005
106views more  CI 2005»
13 years 7 months ago
Incremental Learning of Procedural Planning Knowledge in Challenging Environments
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
Douglas J. Pearson, John E. Laird
ICML
2010
IEEE
13 years 5 months ago
Temporal Difference Bayesian Model Averaging: A Bayesian Perspective on Adapting Lambda
Temporal difference (TD) algorithms are attractive for reinforcement learning due to their ease-of-implementation and use of "bootstrapped" return estimates to make effi...
Carlton Downey, Scott Sanner