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» Using genetic programming to obtain implicit diversity
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GECCO
2007
Springer
160views Optimization» more  GECCO 2007»
14 years 1 months ago
An analysis of constructive crossover and selection pressure in genetic programming
A common problem in genetic programming search algorithms is destructive crossover in which the offspring of good parents generally has worse performance than the parents. Design...
Huayang Xie, Mengjie Zhang, Peter Andreae
ICRA
2006
IEEE
131views Robotics» more  ICRA 2006»
14 years 1 months ago
Proximity Queries between Convex Objects: an Interior Point Approach for Implicit Surfaces
— This paper presents an interior point approach to exact distance computation between convex objects represented as intersections of implicit surfaces. Exact distance computatio...
Nilanjan Chakraborty, Jufeng Peng, Srinivas Akella...
EC
1998
134views ECommerce» more  EC 1998»
13 years 7 months ago
Schema Theory for Genetic Programming with One-Point Crossover and Point Mutation
In this paper we first review the main results obtained in the theory of schemata in Genetic Programming (GP) emphasising their strengths and weaknesses. Then we propose a new, s...
Riccardo Poli, William B. Langdon
CORR
2006
Springer
153views Education» more  CORR 2006»
13 years 7 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
EUROGP
2010
Springer
160views Optimization» more  EUROGP 2010»
13 years 8 months ago
Improving the Generalisation Ability of Genetic Programming with Semantic Similarity based Crossover
This paper examines the impact of semantic control on the ability of Genetic Programming (GP) to generalise via a semantic based crossover operator (Semantic Similarity based Cross...
Nguyen Quang Uy, Nguyen Thi Hien, Nguyen Xuan Hoai...