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» Automatically finding patches using genetic programming
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CEC
2009
IEEE
14 years 4 months ago
Representation and structural biases in CGP
— An evolutionary algorithm automatically discovers suitable solutions to a problem, which may lie anywhere in a large search space of candidate solutions. In the case of Genetic...
Andrew J. Payne, Susan Stepney
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
14 years 1 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...
GECCO
2010
Springer
249views Optimization» more  GECCO 2010»
13 years 12 months ago
Towards improved dispatching rules for complex shop floor scenarios: a genetic programming approach
Developing dispatching rules for manufacturing systems is a tedious process, which is time- and cost-consuming. Since there is no good general rule for different scenarios and ob...
Torsten Hildebrandt, Jens Heger, Bernd Scholz-Reit...
GECCO
2008
Springer
201views Optimization» more  GECCO 2008»
13 years 11 months ago
Advanced techniques for the creation and propagation of modules in cartesian genetic programming
The choice of an appropriate hardware representation model is key to successful evolution of digital circuits. One of the most popular models is cartesian genetic programming, whi...
Paul Kaufmann, Marco Platzner
SEAL
1998
Springer
14 years 2 months ago
Genetic Programming with Active Data Selection
Genetic programming evolves Lisp-like programs rather than fixed size linear strings. This representational power combined with generality makes genetic programming an interesting ...
Byoung-Tak Zhang, Dong-Yeon Cho