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ICANN
2009
Springer
15 years 10 months ago
Measuring and Optimizing Behavioral Complexity for Evolutionary Reinforcement Learning
Model complexity is key concern to any artificial learning system due its critical impact on generalization. However, EC research has only focused phenotype structural complexity ...
Faustino J. Gomez, Julian Togelius, Jürgen Sc...
ICANN
2009
Springer
15 years 10 months ago
Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction
Abstract. In this paper, we investigate the application of adaptive ensemble models of Extreme Learning Machines (ELMs) to the problem of one-step ahead prediction in (non)stationa...
Mark van Heeswijk, Yoan Miche, Tiina Lindh-Knuutil...
114
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IJCNN
2008
IEEE
15 years 10 months ago
Uncertainty propagation for quality assurance in Reinforcement Learning
— In this paper we address the reliability of policies derived by Reinforcement Learning on a limited amount of observations. This can be done in a principled manner by taking in...
Daniel Schneegaß, Steffen Udluft, Thomas Mar...
ANNS
2007
15 years 5 months ago
Direct and indirect classification of high-frequency LNA performance using machine learning techniques
The task of determining low noise amplifier (LNA) high-frequency performance in functional testing is as challenging as designing the circuit itself due to the difficulties associa...
Peter C. Hung, Seán F. McLoone, Magdalena S...
GECCO
2005
Springer
174views Optimization» more  GECCO 2005»
15 years 9 months ago
Emergence of communication in competitive multi-agent systems: a pareto multi-objective approach
In this paper we investigate the emergence of communication in competitive multi-agent systems. A competitive environment is created with two teams of agents competing in an explo...
Michelle McPartland, Stefano Nolfi, Hussein A. Abb...