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» Ensemble Algorithms in Reinforcement Learning
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ECAI
2006
Springer
15 years 8 months ago
Using Emotions for Behaviour-Selection Learning
Emotions play a very important role in human behaviour and social interaction. In this paper we present a control architecture which uses emotions in the behaviour selection proces...
Maria Malfaz, Miguel Angel Salichs
PAKDD
2004
ACM
137views Data Mining» more  PAKDD 2004»
15 years 9 months ago
Fast and Light Boosting for Adaptive Mining of Data Streams
Supporting continuous mining queries on data streams requires algorithms that (i) are fast, (ii) make light demands on memory resources, and (iii) are easily to adapt to concept dr...
Fang Chu, Carlo Zaniolo
ML
2002
ACM
145views Machine Learning» more  ML 2002»
15 years 4 months ago
Boosting Methods for Regression
In this paper we examine ensemble methods for regression that leverage or "boost" base regressors by iteratively calling them on modified samples. The most successful lev...
Nigel Duffy, David P. Helmbold
CORR
2010
Springer
204views Education» more  CORR 2010»
15 years 3 months ago
Predictive State Temporal Difference Learning
We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
Byron Boots, Geoffrey J. Gordon
ECIR
2006
Springer
15 years 5 months ago
Automatic Document Organization in a P2P Environment
Abstract. This paper describes an efficient method to construct reliable machine learning applications in peer-to-peer (P2P) networks by building ensemble based meta methods. We co...
Stefan Siersdorfer, Sergej Sizov