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GECCO
2010
Springer
158views Optimization» more  GECCO 2010»
13 years 11 months ago
Efficiently evolving programs through the search for novelty
A significant challenge in genetic programming is premature convergence to local optima, which often prevents evolution from solving problems. This paper introduces to genetic pro...
Joel Lehman, Kenneth O. Stanley
GECCO
2005
Springer
102views Optimization» more  GECCO 2005»
14 years 1 months ago
Latent variable crossover for k-tablet structures and its application to lens design problems
This paper presents the Real-coded Genetic Algorithms for high-dimensional ill-scaled structures, what is called, the ktablet structure. The k-tablet structure is the landscape th...
Jun Sakuma, Shigenobu Kobayashi
GECCO
2000
Springer
143views Optimization» more  GECCO 2000»
13 years 11 months ago
A Genetic Algorithm for Automatically Designing Modular Reinforcement Learning Agents
Reinforcement learning (RL) is one of the machine learning techniques and has been received much attention as a new self-adaptive controller for various systems. The RL agent auto...
Isao Ono, Tetsuo Nijo, Norihiko Ono
CIBCB
2008
IEEE
14 years 2 months ago
Parallel multi-objective algorithms for the molecular docking problem
— Molecular docking is an essential tool for drug design. It helps the scientist to rapidly know if two molecules, respectively called ligand and receptor, can be combined togeth...
Jean-Charles Boisson, Laetitia Jourdan, El-Ghazali...
GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
13 years 9 months ago
Combining cartesian genetic programming with an estimation of distribution algorithm
This paper describes initial testing of a novel idea to combine a CGP with an EDA. In recent work a new improved crossover technique was successfully applied to a CGP. To implemen...
Janet Clegg