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» Evolving Sinusoidal Oscillators Using Genetic Algorithms
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GECCO
2003
Springer
14 years 2 months ago
Methods for Evolving Robust Programs
Many evolutionary computation search spaces require fitness assessment through the sampling of and generalization over a large set of possible cases as input. Such spaces seem par...
Liviu Panait, Sean Luke
CDC
2008
IEEE
116views Control Systems» more  CDC 2008»
14 years 3 months ago
Effective sensing regions and connectivity of agents undergoing periodic relative motions
— Time-varying graphs are widely used to model communication and sensing in multi-agent systems such as mobile sensor networks and dynamic animal groups. Connectivity is often de...
Daniel T. Swain, Ming Cao, Naomi Ehrich Leonard
ANOR
2010
123views more  ANOR 2010»
13 years 9 months ago
Nature inspired genetic algorithms for hard packing problems
This paper presents two novel genetic algorithms (GAs) for hard industrially relevant packing problems. The design of both algorithms is inspired by aspects of molecular genetics,...
Philipp Rohlfshagen, John A. Bullinaria
CEC
2005
IEEE
13 years 10 months ago
Population based incremental learning with guided mutation versus genetic algorithms: iterated prisoners dilemma
Axelrod’s original experiments for evolving IPD player strategies involved the use of a basic GA. In this paper we examine how well a simple GA performs against the more recent P...
Timothy Gosling, Nanlin Jin, Edward P. K. Tsang
GECCO
2005
Springer
109views Optimization» more  GECCO 2005»
14 years 2 months ago
Investigations in meta-GAs: panaceas or pipe dreams?
A meta-GA (GA within a GA) is used to investigate evolving the parameter settings of genetic operators for genetic and evolutionary algorithms (GEA) in the hope of creating a self...
Jeff Clune, Sherri Goings, Bill Punch, Eric Goodma...