DocumentCode :
2459927
Title :
Why Simulation-Based Approachs with Combined Fitness are a Good Approach for Mining Spaces of Turing-equivalent Functions
Author :
Teytaud, Olivier
Author_Institution :
É quipe TAO (INRIA Futurs), LRI, UMR 8623 (CNRS - Université Paris-Sud), Bat. 490, Université Paris Sud, 91405 Orsay CEDEX, France, olivier.teytaud@lri.fr
fYear :
2006
fDate :
16-21 July 2006
Firstpage :
283
Lastpage :
290
Abstract :
We show negative results about the automatic generation of programs within bounded-time. Combining recursion theory and statistics, we contrast these negative results with positive computability results for iterative approachs like genetic programming, provided that the fitness combines e.g. fastness and size. We then show that simulation-based approachs (approachs evaluating only by simulation the quality of programs) like GP are not too far from the minimal time required for evaluating these combined fitnesses.
Keywords :
Computational efficiency; Computational modeling; Convergence; Costs; Equations; Genetic programming; Iterative algorithms; Iterative methods; Statistical learning; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Print_ISBN :
0-7803-9487-9
Type :
conf
DOI :
10.1109/CEC.2006.1688320
Filename :
1688320
Link To Document :
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