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
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