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» On Generalization by Neural Networks
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GECCO
2005
Springer
174views Optimization» more  GECCO 2005»
16 years 3 days 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
15 years 11 months ago
NEAT in increasingly non-linear control situations
Evolution of neural networks, as implemented in NEAT, has proven itself successful on a variety of low-level control problems such as pole balancing and vehicle control. Nonethele...
Matthias J. Linhardt, Martin V. Butz
ESANN
2006
15 years 8 months ago
Topological Correlation
Quantifying the success of the topographic preservation achieved with a neural map is difficult. In this paper we present Topological Correlation, Tc, a method that assesses the de...
Kevin Doherty, Rod Adams, Neil Davey
NPL
2000
146views more  NPL 2000»
15 years 6 months ago
Competitive and Temporal Inhibition Structures with Spiking Neurons
The paper describes the implementation of competitive neural structures based on a spiking neural model that includes multiplicative or shunting synapses enabling non-saturated sta...
Eduardo Ros Vidal, Francisco J. Pelayo, P. Martin-...
JCNS
2010
103views more  JCNS 2010»
15 years 1 months ago
Efficient computation of the maximum a posteriori path and parameter estimation in integrate-and-fire and more general state-spa
A number of important data analysis problems in neuroscience can be solved using state-space models. In this article, we describe fast methods for computing the exact maximum a pos...
Shinsuke Koyama, Liam Paninski