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GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
15 years 12 months ago
A statistical learning theory approach of bloat
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in the framework of sy...
Sylvain Gelly, Olivier Teytaud, Nicolas Bredeche, ...
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
15 years 12 months ago
Takeover time curves in random and small-world structured populations
We present discrete stochastic mathematical models for the growth curves of synchronous and asynchronous evolutionary algorithms with populations structured according to a random ...
Mario Giacobini, Marco Tomassini, Andrea Tettamanz...
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 12 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
GECCO
2005
Springer
133views Optimization» more  GECCO 2005»
15 years 12 months ago
Tactical UGV navigation and logistics planning
The Army’s push towards developing highly flexible military teams that combine manned and unmanned units requires significant advances in the intelligence of the unmanned units ...
Talib S. Hussain, Daniel Cerys, David J. Montana, ...
GECCO
2005
Springer
130views Optimization» more  GECCO 2005»
15 years 12 months ago
ATNoSFERES revisited
ATNoSFERES is a Pittsburgh style Learning Classifier System (LCS) in which the rules are represented as edges of an Augmented Transition Network. Genotypes are strings of tokens ...
Samuel Landau, Olivier Sigaud, Marc Schoenauer