Darwinian evolution as a paradigm for AI research
- 1 July 1986
- journal article
- Published by Association for Computing Machinery (ACM) in ACM SIGART Bulletin
- Vol. 97 (97) , 22-23
- https://doi.org/10.1145/15719.15721
Abstract
Modern Darwinian evolutionary theory is a robust set of concepts that must be transported as a whole if they are to be used paradigmatically in any other context than that of their origin. For Al, the most immediately relevant lessons of evolutionary theory and process are listed below. Their meaning for AI research is that evolution can provide a paradigm for and the outline of an evolving system beyond the metaphorical sense of "evolution," if the full Darwinian paradigm is adopted. This discussion outlines how AI research can make use of the full Darwinian evolutionary paradigm by constructing "learning systems" upon a simulated genetic basis. It also suggests how the Darwinian evolutionary process is already active in one non-biotic context, namely, large organizations (public and private) that extensively use data base management systems (DBMS).Keywords
This publication has 3 references indexed in Scilit:
- Evolution ex machinaSystems Research, 1986
- Biologically motivated machine intelligenceACM SIGART Bulletin, 1986
- Darwinism and the Expansion of Evolutionary TheoryScience, 1982