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GECCO
2010
Springer
168views Optimization» more  GECCO 2010»
14 years 11 days ago
Investigating whether hyperNEAT produces modular neural networks
HyperNEAT represents a class of neuroevolutionary algorithms that captures some of the power of natural development with a ionally efficient high-level abstraction of development....
Jeff Clune, Benjamin E. Beckmann, Philip K. McKinl...
GECCO
2005
Springer
174views Optimization» more  GECCO 2005»
14 years 1 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...
GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
14 years 2 months ago
Neural network ensembles for time series forecasting
This work provides an analysis of using the evolutionary algorithm EPNet to create ensembles of artificial neural networks to solve a range of forecasting tasks. Several previous...
Victor M. Landassuri-Moreno, John A. Bullinaria
KDD
2005
ACM
99views Data Mining» more  KDD 2005»
14 years 8 months ago
Determining an author's native language by mining a text for errors
In this paper, we show that stylistic text features can be exploited to determine an anonymous author's native language with high accuracy. Specifically, we first use automat...
Moshe Koppel, Jonathan Schler, Kfir Zigdon
CEC
2009
IEEE
14 years 8 days ago
Memory-enhanced Evolutionary Robotics: The Echo State Network Approach
— Interested in Evolutionary Robotics, this paper focuses on the acquisition and exploitation of memory skills. The targeted task is a well-studied benchmark problem, the Tolman ...
Cédric Hartland, Nicolas Bredeche, Mich&egr...