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Proceedings Paper

Routine human-competitive machine intelligence by means of genetic programming
Author(s): John R. Koza; Matthew J. Streeter; Martin Keane
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Paper Abstract

Genetic programming is a systematic method for getting computers to automatically solve a problem. Genetic programming starts from a high-level statement of what needs to be done and automatically creates a computer program to solve the problem. The paper demonstrates that genetic programming (1) now routinely delivers high-return human-competitive machine intelligence; (2) is an automated invention machine; (3) can automatically create a general solution to a problem in the form of a parameterized topology; and (4) has delivered a progression of qualitatively more substantial results in synchrony with five approximately order-of-magnitude increases in the expenditure of computer time. Recent results involving the automatic synthesis of the topology and sizing of analog electrical circuits and controllers demonstrate these points.

Paper Details

Date Published: 30 December 2003
PDF: 15 pages
Proc. SPIE 5200, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation VI, (30 December 2003); doi: 10.1117/12.512613
Show Author Affiliations
John R. Koza, Stanford Univ. (United States)
Matthew J. Streeter, Genetic Programming, Inc. (United States)
Martin Keane, Econometrics, Inc. (United States)


Published in SPIE Proceedings Vol. 5200:
Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation VI
Bruno Bosacchi; David B. Fogel; James C. Bezdek, Editor(s)

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