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EUROGP
1999
Springer
137views Optimization» more  EUROGP 1999»
14 years 15 hour ago
Evolving Controllers for Autonomous Agents Using Genetically Programmed Networks
– This article presents a new approach to the evolution of controllers for autonomous agents. We propose the evolution of a connectionist structure where each node has an associa...
Arlindo Silva, Ana Neves, Ernesto Costa
ESANN
2003
13 years 9 months ago
Autonomous learning algorithm for fully connected recurrent networks
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
Edouard Leclercq, Fabrice Druaux, Dimitri Lefebvre
GECCO
2006
Springer
141views Optimization» more  GECCO 2006»
13 years 11 months ago
Coevolution of neural networks using a layered pareto archive
The Layered Pareto Coevolution Archive (LAPCA) was recently proposed as an effective Coevolutionary Memory (CM) which, under certain assumptions, approximates monotonic progress i...
German A. Monroy, Kenneth O. Stanley, Risto Miikku...
AIPRF
2007
13 years 9 months ago
Instinct and Learning Synergy in Simulated Foraging Using a Neural Network
Instinct and experience are shown to form a potent combination to achieve effective foraging in a simulated environment. A neural network capable of evolving instinct-related neur...
Thomas E. Portegys
IJON
2006
67views more  IJON 2006»
13 years 7 months ago
Robust persistent activity in neural fields with asymmetric connectivity
Modeling studies have shown that recurrent interactions within neural networks are capable of self-sustaining non-uniform activity profiles. These patterns are thought to be the n...
Cláudia Horta, Wolfram Erlhagen