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GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
15 years 3 months ago
Memory with memory: soft assignment in genetic programming
Based in part on observations about the incremental nature of most state changes in biological systems, we introduce the idea of Memory with Memory in Genetic Programming (GP), wh...
Nicholas Freitag McPhee, Riccardo Poli
109
Voted
CEC
2009
IEEE
15 years 9 months ago
Gate-level optimization of polymorphic circuits using Cartesian Genetic Programming
— Polymorphic digital circuits contain ordinary and polymorphic gates. In the past, Cartesian Genetic Programming (CGP) has been applied to synthesize polymorphic circuits at the...
Zbysek Gajda, Lukás Sekanina
CEC
2007
IEEE
15 years 8 months ago
Success effort and other statistics for performance comparisons in genetic programming
— This paper looks at the statistics used to compare variations to the genetic programming method. Previous work in this area has been dominated by the use of mean best-of-run ï¬...
Matthew Walker, Howard Edwards, Chris H. Messom
AE
2007
Springer
15 years 8 months ago
Automatic Design of Vision-Based Obstacle Avoidance Controllers Using Genetic Programming
The work presented in this paper is part of the development of a robotic system able to learn context dependent visual clues to navigate in its environment. We focus on the obstacl...
Renaud Barate, Antoine Manzanera
144
Voted
ECML
2007
Springer
15 years 8 months ago
Multi-objective Genetic Programming for Multiple Instance Learning
Abstract. This paper introduces the use of multi-objective evolutionary algorithms in multiple instance learning. In order to achieve this purpose, a multi-objective grammar-guided...
Amelia Zafra, Sebastián Ventura