- author = "Peter J. Angeline and Jordan Pollack",
- title = "Evolutionary Module Acquisition",
- booktitle = "Proceedings of the Second Annual Conference on Evolutionary Programming",
- year = "1993",
- editor = "D. Fogel and W. Atmar",
- pages = "154--163",
- address = "La Jolla, CA, USA",
- month = "25-26 " # feb,
- organisation = "The Evolutionary Programming Society",
- keywords = "genetic algorithms, genetic programming, FSM, GLiB",
-
URL = "
http://www.demo.cs.brandeis.edu/papers/ep93.pdf",
-
URL = "
http://www.demo.cs.brandeis.edu/papers/ep93.ps.gz",
-
URL = "http://www.natural-selection.com/Library/1993/ep93.ps.Z",
- size = "9 pages",
- abstract = "Evolutionary programming and genetic algorithms share many features, not the least of which is a reliance of an analogy to natural selection over a population as a means of implementing search. With their commonalities come shared problems whose solutions can be investigated at a higher level and applied to both. One such problem is the manipulation of solution parameters whose values encode a desirable sub-solution. In this paper, we define a superset of evolutionary programming and genetic algorithms, called evolutionary algorithms, and demonstrate a method of automatic modularization that protects promising partial solutions and speeds acquisition time.",
-
notes = "Artificial Ant (John Muir). Finite State Machines.
Genetic Library Builder
",
