Review #1

From: Martha Mercaldi (mercaldi@cs.washington.edu)
Date: Wed Dec 01 2004 - 08:38:10 PST

  • Next message: Seth Cooper: "Review of "The Evolutionary Origin of Complex Features""

    The evolutionary origin of complex features

    Richard E. Lenski, Charles Ofria, Robert T. Pennock & Christoph Adami

     

    This paper simulates evolution of organisms, using computer programs to
    represent organisms. For the most part it validates properties of
    evolution (i.e. initially harmful mutation, if survived, required to
    produce beneficial feature) which have been validated by experiments on
    other organisms, such as in biology.

     

    Simulating these processes in computers, if we trust that the
    environment we contrive is representative of the real world, allows the
    researcher to peer deeper in the process, to turn back time, to know
    exactly what mutations occur and in what order, and to simulate
    hypothetical situations. Biologists in a lab cannot do this, and the
    ability to study our model in this way has the potential to reveal
    properties of evolution that have not been observable in a
    laboratory.  Of course it would be wise to devise (if possible) a
    biological experiment to test any hypotheses generated from simulation,

    Evolution as search:

    Evolution can be seen as a search problem. The state space is infinite
    (all possible genotypes) and the transitions are mutations. This is
    just for asexual reproduction. The transition rules for sexual
    reproduction would be more complex. The fitness function and the
    environment comprise a heuristic that guides the random walk. The
    “frontier” of the search is the current population. The environment
    using the fitness function supports replication of organisms with
    beneficial mutations first, essentially ordering the queue in a BFS and
    encouraging exploration of the best states first.

     

    Evolution not as search:

    In deterministic search there is no benefit to re-exploring a node that
    has already been visited, however, in this case a genotype could
    conceivably evolve back to one that existed in the past. If it survives
    it is reasonable to continue exploring it as the way in which it
    mutates is likely to be different from how it did previously.

     

    Some questions that this work might explore next. How sensitive is the
    evolutionary process to the genetic encoding. The authors here picked
    some machine language, but what if the instructions were more or less
    dense (CISC v. RISC instructions)? What effect would that have on the
    speed and success of evolution? Also, this was mentioned in the
    conclusion, but it seems that sexual reproduction would change the
    model and some of the conclusions. However in the spirit of “best
    first” exploration, there are plenty of organisms (i.e. viri and
    bacteria) which replicate asexually which we’d love to better
    understand, so this seems less pressing.


  • Next message: Seth Cooper: "Review of "The Evolutionary Origin of Complex Features""

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