15 search results - page 3 / 3 » Motor control and movement optimization learned by combining... |
GECCO
2005
Springer
13 years 11 months ago
2005
Springer
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
GECCO
2010
Springer
13 years 5 months ago
2010
Springer
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
GECCO
2005
Springer
13 years 11 months ago
2005
Springer
This paper presents an approach to combine competent crossover and mutation operators via probabilistic model building. Both operators are based on the probabilistic model buildin...
GECCO
2006
Springer
13 years 9 months ago
2006
Springer
This paper presents a hybrid technique that combines List Scheduling (LS) with Genetic Algorithms (GA) for constructing non-preemptive schedules for soft real-time parallel applic...
GECCO
2005
Springer
13 years 11 months ago
2005
Springer
This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominat...