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UC
2005
Springer
13 years 10 months ago
Using Genetic Algorithms to Evolve Behavior in Cellular Automata
Abstract. It is an unconventional computation approach to evolve solutions instead of calculating them. Although using evolutionary computation in computer science dates back to th...
Thomas Bäck, Ron Breukelaar
UPP
2004
Springer
13 years 10 months ago
Inverse Design of Cellular Automata by Genetic Algorithms: An Unconventional Programming Paradigm
Evolving solutions rather than computing them certainly represents an unconventional programming approach. The general methodology of evolutionary computation has already been know...
Thomas Bäck, Ron Breukelaar, Lars Willmes
HAIS
2011
Springer
12 years 8 months ago
Evolving Temporal Fuzzy Association Rules from Quantitative Data with a Multi-Objective Evolutionary Algorithm
A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented. This method successfully identifie...
Stephen G. Matthews, Mario A. Góngora, Adri...
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
13 years 8 months ago
Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state GP
In contrast with the diverse array of genetic algorithms, the Genetic Programming (GP) paradigm is usually applied in a relatively uniform manner. Heuristics have developed over t...
L. Darrell Whitley, Marc D. Richards, J. Ross Beve...
IFIP
2004
Springer
13 years 10 months ago
Solving Geometrical Place Problems by using Evolutionary Algorithms
Geometrical place can be sometimes difficult to find by applying mathematical methods. Evolutionary algorithms deal with a population of solutions. This population (initially ran...
Crina Grosan