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GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
16 years 5 days ago
Not all linear functions are equally difficult for the compact genetic algorithm
Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
Stefan Droste
GECCO
2005
Springer
119views Optimization» more  GECCO 2005»
16 years 5 days ago
A new evolutionary method for time series forecasting
This paper presents a new method — the Time-delay Added Evolutionary Forecasting (TAEF) method — for time series prediction which performs an evolutionary search of the minimu...
Tiago A. E. Ferreira, Germano C. Vasconcelos, Paul...
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
16 years 5 days ago
An artificial immune network for multimodal function optimization on dynamic environments
Multimodal optimization algorithms inspired by the immune system are generally characterized by a dynamic control of the population size and by diversity maintenance along the sea...
Fabrício Olivetti de França, Fernand...
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
16 years 5 days 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»
16 years 5 days 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
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