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» Combining mutation operators in evolutionary programming
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GECCO
2010
Springer
129views Optimization» more  GECCO 2010»
13 years 11 months ago
A probabilistic functional crossover operator for genetic programming
The original mechanism by which evolutionary algorithms were to solve problems was to allow for the gradual discovery of sub-solutions to sub-problems, and the automated combinati...
Josh C. Bongard
GECCO
2003
Springer
415views Optimization» more  GECCO 2003»
14 years 5 days ago
Evolutionary Algorithms for Two Problems from the Calculus of Variations
Abstract. A brachistochrone is the path along which a weighted particle falls most quickly from one point to another, and a catenary is the smooth curve connecting two points whose...
Bryant A. Julstrom
ML
2000
ACM
244views Machine Learning» more  ML 2000»
13 years 6 months ago
Learnable Evolution Model: Evolutionary Processes Guided by Machine Learning
A new class of evolutionary computation processes is presented, called Learnable Evolution Model or LEM. In contrast to Darwinian-type evolution that relies on mutation, recombinat...
Ryszard S. Michalski
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 8 months ago
A parallel evolutionary algorithm for unconstrained binary quadratic problems
In this paper an island model is described for the unconstrained Binary Quadratic Problem (BQP), which can be used with up to 2500 binary variables. Our island model uses a master...
István Borgulya
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
13 years 10 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson