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GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 10 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
158views Optimization» more  GECCO 2005»
15 years 10 months ago
Applying both positive and negative selection to supervised learning for anomaly detection
This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
Xiaoshu Hang, Honghua Dai
SAC
2004
ACM
15 years 10 months ago
Solving the maximum clique problem by k-opt local search
This paper presents a local search algorithm based on variable depth search, called the k-opt local search, for the maximum clique problem. The k-opt local search performs add and...
Kengo Katayama, Akihiro Hamamoto, Hiroyuki Narihis...
148
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EVOW
2004
Springer
15 years 10 months ago
A Comparison of Adaptive Operator Scheduling Methods on the Traveling Salesman Problem
Abstract. The implementation of an evolutionary algorithm necessarily involves the selection of an appropriate set of genetic operators. For many real-world problem domains, an inc...
Wouter Boomsma
GECCO
2004
Springer
110views Optimization» more  GECCO 2004»
15 years 10 months ago
Using GP to Model Contextual Human Behavior
To create a realistic environment, some simulations require simulated agents with human behavior pattern. Creating such agents with realistic behavior can be a tedious and time con...
Hans Fernlund, Avelino J. Gonzalez