Sciweavers

107 search results - page 15 / 22
» Competitive Self-adaptation in Evolutionary Algorithms
Sort
View
MEMETIC
2010
311views more  MEMETIC 2010»
13 years 2 months ago
Iterated local search with Powell's method: a memetic algorithm for continuous global optimization
In combinatorial solution spaces Iterated Local Search (ILS) turns out to be exceptionally successful. The question arises: is ILS also capable of improving the optimization proces...
Oliver Kramer
GECCO
2009
Springer
135views Optimization» more  GECCO 2009»
14 years 2 months ago
Neuroevolutionary reinforcement learning for generalized helicopter control
Helicopter hovering is an important challenge problem in the field of reinforcement learning. This paper considers several neuroevolutionary approaches to discovering robust cont...
Rogier Koppejan, Shimon Whiteson
EPS
1998
Springer
13 years 12 months ago
Acquisition of General Adaptive Features by Evolution
We investigate the following question. Do populations of evolving agents adapt only to their recent environment or do general adaptive features appear over time? We find statistica...
Dan Ashlock, John E. Mayfield
CEC
2008
IEEE
14 years 2 months ago
On the scalability of particle swarm optimisation
— Particle swarm has proven to be competitive to other evolutionary algorithms in the field of optimization, and in many cases enables a faster convergence to the ideal solution...
Sébastien Piccand, Michael O'Neill, Jacquel...
CEC
2009
IEEE
14 years 11 days ago
Memetic algorithm with Local search chaining for large scale continuous optimization problems
Abstract— Memetic algorithms arise as very effective algorithms to obtain reliable and high accurate solutions for complex continuous optimization problems. Nowadays, high dimens...
Daniel Molina, Manuel Lozano, Francisco Herrera