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240views
14 years 1 months ago
Bayesian multitask inverse reinforcement learning
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or ...
Christos Dimitrakakis, Constantin A. Rothkopf
108
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ATAL
2010
Springer
15 years 3 months ago
Basis function construction for hierarchical reinforcement learning
This paper introduces an approach to automatic basis function construction for Hierarchical Reinforcement Learning (HRL) tasks. We describe some considerations that arise when con...
Sarah Osentoski, Sridhar Mahadevan
134
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EUSFLAT
2009
140views Fuzzy Logic» more  EUSFLAT 2009»
15 years 17 days ago
Incremental Possibilistic Approach for Online Clustering and Classification
In this paper, we propose to develop the supervised classification method Fuzzy Pattern Matching to be in addition a non supervised one. The goal is to monitor dynamic systems with...
Moamar Sayed Mouchaweh, Bernard Riera
134
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ICRA
2010
IEEE
137views Robotics» more  ICRA 2010»
15 years 1 months ago
Robot reinforcement learning using EEG-based reward signals
Abstract— Reinforcement learning algorithms have been successfully applied in robotics to learn how to solve tasks based on reward signals obtained during task execution. These r...
Iñaki Iturrate, Luis Montesano, Javier Ming...
111
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ICES
2003
Springer
125views Hardware» more  ICES 2003»
15 years 8 months ago
Evolving Reinforcement Learning-Like Abilities for Robots
Abstract. In [8] Yamauchi and Beer explored the abilities of continuous time recurrent neural networks (CTRNNs) to display reinforcementlearning like abilities. The investigated ta...
Jesper Blynel