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» Using Neural Nets to Estimate Evolutionary Parameters
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GECCO
2007
Springer
158views Optimization» more  GECCO 2007»
14 years 2 months ago
A novel generative encoding for exploiting neural network sensor and output geometry
A significant problem for evolving artificial neural networks is that the physical arrangement of sensors and effectors is invisible to the evolutionary algorithm. For example,...
David B. D'Ambrosio, Kenneth O. Stanley
CMSB
2009
Springer
13 years 12 months ago
On the Use of Stochastic Petri Nets in the Analysis of Signal Transduction Pathways for Angiogenesis Process
In this paper we consider the modeling of a selected portion of signal transduction events involved in the angiogenesis process. The detailed model of this process contains a large...
Lucia Napione, Daniele Manini, Francesca Cordero, ...
ATAL
2008
Springer
13 years 10 months ago
Analysis of an evolutionary reinforcement learning method in a multiagent domain
Many multiagent problems comprise subtasks which can be considered as reinforcement learning (RL) problems. In addition to classical temporal difference methods, evolutionary algo...
Jan Hendrik Metzen, Mark Edgington, Yohannes Kassa...
EUROCOLT
1997
Springer
14 years 17 days ago
Vapnik-Chervonenkis Dimension of Recurrent Neural Networks
Most of the work on the Vapnik-Chervonenkis dimension of neural networks has been focused on feedforward networks. However, recurrent networks are also widely used in learning app...
Pascal Koiran, Eduardo D. Sontag
IWINAC
2007
Springer
14 years 2 months ago
Evolving Robot Behaviour at Micro (Molecular) and Macro (Molar) Action Level
We investigate how it is possible to shape robot behaviour adopting a molecular or molar point of view. These two ways to approach the issue are inspired by Learning Psychology, wh...
Michela Ponticorvo, Orazio Miglino