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- From: m16532@mwunix (Steven Bayer)
- Subject: Re: Tournament selection
- Message-ID: <1993Jan12.154359.13650@linus.mitre.org>
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- Organization: MITRE Corporation, Houston, TX
- References: <1iscvrINNcp2@life.ai.mit.edu>
- Date: Tue, 12 Jan 1993 15:43:59 GMT
- Lines: 54
-
- In article <1iscvrINNcp2@life.ai.mit.edu> mdlm@great-grain.ai.mit.edu (Michael De-la-Maza) writes:
- >Lots of books (e.g., Goldberg's textbook and Koza's Genetic Programming)
- >refer to tournament selection. However, I have been unable to find the
- >original source of the method. Does anyone know what the original
- >citation is?
-
- There are two types of "tournament" selection...
-
- 1. Goldberg's book talks about "stochastic tournament" as suggested by
- Art Wetzel to Anne Brindle (1981). According to Brindle's dissertation,
- "The last method of selection is a ranking method proposed by Art Wetzel
- (1979) which differs radically from the other selection methods. Each
- parent is selected by sampling twice from the distribution (stochastic
- sampling with replacement) and using the better of the two individuals."
-
- Of course, the "tournament size" does not have to be two. I don't have
- references handy on this, but my experience has been that this method
- is prone to too rapid convergence. With this method, there is also no
- guarantee that the best members of the population (even the "super"
- individual) will survive the current generation.
-
- The citations are
- "Wetzel, A. 1979. Personal communication." (from Brindle)
- Brindle, A. (1981) Genetic Algorithms for Function Optimization, Ph.D.
- Dissertation, Technical Report TR81-2, Department of Computing Science,
- University of Alberta, Canada, January, 1981 (Goldberg lists this as
- unpublished, but I have a copy of the report; also, the date should be
- 1981, not 1983 as in Goldberg.)
-
- 2. I have no reference for the other "tournament" selection method. I
- first learned about it first from the Software Technology Branch at NASA's
- Johnson Space Center. It may have origninated there, but I doubt it because
- I also heard about it from Rob Smith at the University of Alabama (where
- Goldberg was as well). Papers that discuss it don't cite a reference.
-
- Basically, you shuffle the population. Then take "tournament size" members
- sequentially off the top of the population. Select the member with the best
- fitness as a parent (i.e., hold a tournament). Keep moving this way through
- the population. When you've exhausted the population, reshuffle and start
- again, until the parent list is full.
-
- This method has some nice qualities. For one, the best member (the "super"
- individual) is guarenteed to survive (i.e., built in elitism) and the best
- member realizes its target mating rate.
-
- Hope this helps.
- __o
- ~\<,
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