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GECCO
2000
Springer
138views Optimization» more  GECCO 2000»
15 years 8 months ago
Time Complexity of genetic algorithms on exponentially scaled problems
This paper gives a theoretical and empirical analysis of the time complexity of genetic algorithms (GAs) on problems with exponentially scaled building blocks. It is important to ...
Fernando G. Lobo, David E. Goldberg, Martin Pelika...
GECCO
2000
Springer
143views Optimization» more  GECCO 2000»
15 years 8 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
EUROGP
2010
Springer
182views Optimization» more  EUROGP 2010»
15 years 7 months ago
Unsupervised Problem Decomposition Using Genetic Programming
We propose a new framework based on Genetic Programming (GP) to automatically decompose problems into smaller and simpler tasks. The framework uses GP at two levels. At the top lev...
Ahmed Kattan, Alexandros Agapitos, Riccardo Poli
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
15 years 6 months ago
Parsimonious regularization using genetic algorithms applied to the analysis of analytical ultracentrifugation experiments
Frequently in the physical sciences experimental data are analyzed to determine model parameters using techniques known as parameter estimation. Eliminating the effects of noise ...
Emre H. Brookes, Borries Demeler
EUROGP
2008
Springer
15 years 6 months ago
PlasmidPL: A Plasmid-Inspired Language for Genetic Programming
We present PlasmidPL, a plasmid-inspired programming language designed for Genetic Programming (GP), and based on a chemical metaphor. The basic data structures in PlasmidPL are ci...
Lidia Yamamoto