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» Dynamic abstraction in reinforcement learning via clustering
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EUSFLAT
2009
140views Fuzzy Logic» more  EUSFLAT 2009»
13 years 5 months 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
ECAI
2010
Springer
13 years 8 months ago
The Dynamics of Multi-Agent Reinforcement Learning
Abstract. Infinite-horizon multi-agent control processes with nondeterminism and partial state knowledge have particularly interesting properties with respect to adaptive control, ...
Luke Dickens, Krysia Broda, Alessandra Russo
ICANN
2010
Springer
13 years 8 months ago
Reinforcement Learning Based Neural Controllers for Dynamic Processes without Exploration
Abstract. In this paper we present a Reinforcement Learning (RL) approach with the capability to train neural adaptive controllers for complex control problems without expensive on...
Frank-Florian Steege, André Hartmann, Erik ...
SDM
2004
SIAM
189views Data Mining» more  SDM 2004»
13 years 8 months ago
An Abstract Weighting Framework for Clustering Algorithms
act Weighting Framework for Clustering Algorithms Richard Nock Frank Nielsen Recent works in unsupervised learning have emphasized the need to understand a new trend in algorithmi...
Richard Nock, Frank Nielsen
IJCNN
2006
IEEE
14 years 1 months ago
Learning a Rendezvous Task with Dynamic Joint Action Perception
Abstract— Groups of reinforcement learning agents interacting in a common environment often fail to learn optimal behaviors. Poor performance is particularly common in environmen...
Nancy Fulda, Dan Ventura