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» Evolving neural network ensembles for control problems
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ASUNAM
2010
IEEE
14 years 8 months ago
A Multiobjective and Evolutionary Clustering Method for Dynamic Networks
—The discovery of evolving communities in dynamic networks is an important research topic that poses challenging tasks. Previous evolutionary based clustering methods try to maxi...
Francesco Folino, Clara Pizzuti
99
Voted
GECCO
2007
Springer
217views Optimization» more  GECCO 2007»
14 years 11 months ago
A quantitative analysis of memory requirement and generalization performance for robotic tasks
In autonomous agent systems, memory is an important element to handle agent behaviors appropriately. We present the analysis of memory requirements for robotic tasks including wal...
DaeEun Kim
IJCNN
2008
IEEE
15 years 4 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...
109
Voted
GECCO
2003
Springer
112views Optimization» more  GECCO 2003»
15 years 2 months ago
Multi-agent Learning of Heterogeneous Robots by Evolutionary Subsumption
Abstract. Many multi-robot systems are heterogeneous cooperative systems, systems consisting of different species of robots cooperating with each other to achieve a common goal. T...
Hongwei Liu, Hitoshi Iba
WOA
2001
14 years 11 months ago
Implementing Adaptive Capabilities on Agents that Act in a Dynamic Environment
Acting in a dynamic environment is a complex task that requires several issues to be investigated, with the aim of controlling the associated search complexity. In this paper, a l...
Giuliano Armano, Giancarlo Cherchi, Eloisa Vargiu