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» Seeding Genetic Programming Populations
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ISCAS
2005
IEEE
179views Hardware» more  ISCAS 2005»
14 years 1 months ago
Robust stabilization of control systems using piecewise linear Lyapunov functions and evolutionary algorithm
— Piecewise linear Lyapunov functions are used to design control gain matrices so that closed systems are robust stable and attractive regions are expanded as large as possible i...
K. Tagawa, Y. Ohta
IFIP
2004
Springer
14 years 1 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
GECCO
2006
Springer
215views Optimization» more  GECCO 2006»
13 years 11 months ago
A multi-chromosome approach to standard and embedded cartesian genetic programming
Embedded Cartesian Genetic Programming (ECGP) is an extension of Cartesian Genetic Programming (CGP) that can automatically acquire, evolve and re-use partial solutions in the for...
James Alfred Walker, Julian Francis Miller, Rachel...
ENTCS
2006
113views more  ENTCS 2006»
13 years 7 months ago
Concurrent Java Test Generation as a Search Problem
A Random test generator generates executable tests together with their expected results. In the form of a noise-maker, it seeds the program with conditional scheduling primitives ...
Yaniv Eytani
IWINAC
2005
Springer
14 years 1 months ago
GA-Selection Revisited from an ES-Driven Point of View
Whereas the selection concept of Genetic Algorithms (GAs) and Genetic Programming (GP) is basically realized by the selection of above-average parents for reproduction, Evolution S...
Michael Affenzeller, Stefan Wagner 0002, Stephan M...