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ICANN
2009
Springer
16 years 1 months ago
Evolving Memory Cell Structures for Sequence Learning
The best recent supervised sequence learning methods use gradient descent to train networks of miniature nets called memory cells. The most popular cell structure seems somewhat ar...
Justin Bayer, Daan Wierstra, Julian Togelius, J&uu...
MIG
2009
Springer
16 years 1 months ago
Evolved Controllers for Simulated Locomotion
Abstract. We present a system for automatically evolving neural networks as physics-based locomotion controllers for humanoid characters. Our approach provides two key features: (a...
Brian F. Allen, Petros Faloutsos
ACSC
2005
IEEE
16 years 6 days ago
Graph Grammar Encoding and Evolution of Automata Networks
The global dynamics of automata networks (such as neural networks) are a function of their topology and the choice of automata used. Evolutionary methods can be applied to the opt...
Martin H. Luerssen
CEC
2005
IEEE
16 years 6 days ago
On the complexity of overcoming gaps with isotropic mutations and elitist selection
We consider the (1+λ) evolution strategy, an evolutionary algorithm for minimization in Rn , using isotropic mutations. Thus, for instance, Gaussian mutations adapted by the 1/5-r...
Jens Jägersküpper
GECCO
2004
Springer
15 years 12 months ago
On the Choice of the Population Size
Abstract. Evolutionary Algorithms (EAs) are population-based randomized optimizers often solving problems quite successfully. Here, the focus is on the possible effects of changin...
Tobias Storch