Re: No Free Lunch (NFL) Lecture

From: bivalve (
Date: Tue Jul 16 2002 - 20:14:07 EDT

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    >His lecture showed that any special search algorithm that is used to
    >optimize a given quality (such as a fitness function) can on the
    >average be no more efficient than a RANDOM search.<

    I am currently running analyses that seek to optimize a given quality
    (minimum parsimony) in an analysis of genetic data. The program uses
    heuristic search algorithms that are far better than random searches.
    What is the difference between this and the genetic algorithms?

    Some possibilities that come to mind:

    A search guarenteed to find the absolute optimum is much less
    efficient than these heuristic approximations. However, living
    organisms also get by just fine with suboptimal, but good, versions.

    The heuristic analyses start with trying to find a good option and
    then try to improve on it. Again, living organisms are generally
    starting with a functional gene, and the number of changes needed to
    make another functional gene is less than for starting from scratch.

    Organisms have extra DNA. This means that they can have parallel
    processing in searching for a particular result.

    Not knowing the detailes of the programs and the precise goal of the
    algorithms, I do not know how applicable any of these replies may be.

         Dr. David Campbell
         Old Seashells
         University of Alabama
         Biodiversity & Systematics
         Dept. Biological Sciences
         Box 870345
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