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125
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ATAL
2010
Springer
15 years 4 months ago
Frequency adjusted multi-agent Q-learning
Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
Michael Kaisers, Karl Tuyls
129
Voted
KAIS
2000
106views more  KAIS 2000»
15 years 3 months ago
FANNC: A Fast Adaptive Neural Network Classifier
In this paper, a fast adaptive neural network classifier named FANNC is proposed. FANNC exploits the advantages of both adaptive resonance theory and field theory. It needs only on...
Zhi-Hua Zhou, Shifu Chen, Zhaoqian Chen
128
Voted
GECCO
2007
Springer
144views Optimization» more  GECCO 2007»
15 years 7 months ago
Mixing independent classifiers
In this study we deal with the mixing problem, which concerns combining the prediction of independently trained local models to form a global prediction. We deal with it from the ...
Jan Drugowitsch, Alwyn Barry
112
Voted
CORR
2002
Springer
79views Education» more  CORR 2002»
15 years 3 months ago
Technical Note: Bias and the Quantification of Stability
Research on bias in machine learning algorithms has generally been concerned with the impact of bias on predictive accuracy. We believe that there are other factors that should al...
Peter D. Turney
121
Voted
ICDM
2009
IEEE
146views Data Mining» more  ICDM 2009»
15 years 10 months ago
Induction of Mean Output Prediction Trees from Continuous Temporal Meteorological Data
: In this paper, we present a novel method for fast data-driven construction of regression trees from temporal datasets including continuous data streams. The proposed Mean Output ...
Dima Alberg, Mark Last, Roni Neuman, Avi Sharon