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GECCO
2000
Springer
104views Optimization» more  GECCO 2000»
13 years 9 months ago
Quadratic Bloat in Genetic Programming
In earlier work we predicted program size would grow in the limit at a quadratic rate and up to fty generations we measured bloat O(generations1:2;1:5). On two simple benchmarks w...
William B. Langdon
GECCO
2007
Springer
138views Optimization» more  GECCO 2007»
13 years 11 months ago
Unwitting distributed genetic programming via asynchronous JavaScript and XML
The success of a genetic programming system in solving a problem is often a function of the available computational resources. For many problems, the larger the population size an...
Jon Klein, Lee Spector
EUROGP
2007
Springer
135views Optimization» more  EUROGP 2007»
13 years 11 months ago
A Grammatical Genetic Programming Approach to Modularity in Genetic Algorithms
The ability of Genetic Programming to scale to problems of increasing difficulty operates on the premise that it is possible to capture regularities that exist in a problem environ...
Erik Hemberg, Conor Gilligan, Michael O'Neill, Ant...
EC
2006
120views ECommerce» more  EC 2006»
13 years 5 months ago
A Comparison of Bloat Control Methods for Genetic Programming
Genetic programming has highlighted the problem of bloat, the uncontrolled growth of the average size of an individual in the population. The most common approach to dealing with ...
Sean Luke, Liviu Panait
GECCO
2009
Springer
103views Optimization» more  GECCO 2009»
13 years 12 months ago
Why evolution is not a good paradigm for program induction: a critique of genetic programming
We revisit the roots of Genetic Programming (i.e. Natural Evolution), and conclude that the mechanisms of the process of evolution (i.e. selection, inheritance and variation) are ...
John R. Woodward, Ruibin Bai