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» Optimal Control With Noisy Time
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GECCO
2006
Springer
163views Optimization» more  GECCO 2006»
15 years 7 months ago
The quadratic multiple knapsack problem and three heuristic approaches to it
The quadratic multiple knapsack problem extends the quadratic knapsack problem with K knapsacks, each with its own capacity Ck. A greedy heuristic fills the knapsacks one at a tim...
Amanda Hiley, Bryant A. Julstrom
GECCO
2006
Springer
173views Optimization» more  GECCO 2006»
15 years 7 months ago
Pareto-coevolutionary genetic programming classifier
The conversion and extension of the Incremental ParetoCoevolution Archive algorithm (IPCA) into the domain of Genetic Programming classifier evolution is presented. In order to ac...
Michal Lemczyk, Malcolm I. Heywood
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GECCO
2006
Springer
152views Optimization» more  GECCO 2006»
15 years 7 months ago
A combinatorial genetic algorithm for the configuration of the 2dF/AAOmega spectrograph at the anglo-Australian observatory
To help unravel the structure of the universe, astronomers have developed systems which observe large clusters of objects at the same time. One such system is the 2-degree field s...
Steven Manos, Geraint Lewis
GECCO
2006
Springer
141views Optimization» more  GECCO 2006»
15 years 7 months ago
Coevolution of neural networks using a layered pareto archive
The Layered Pareto Coevolution Archive (LAPCA) was recently proposed as an effective Coevolutionary Memory (CM) which, under certain assumptions, approximates monotonic progress i...
German A. Monroy, Kenneth O. Stanley, Risto Miikku...
GECCO
2000
Springer
143views Optimization» more  GECCO 2000»
15 years 7 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