Distributed Computation and Evolution

Distributed Computation

The interaction of many simple, parallel, local processes leads to emergent, "smart," global behavior

Evolution: An Example of Distributed Computation

• What's needed for evolutionary computation (abstract or real) to work
  • "Creatures" which
    1. Give birth to other creatures, passing on their traits to them
    2. Die
  • A way of evaluating the creatures' traits: some aid in survival or reproduction, others don't ("survival of the fittest")
  • A way of generating new traits: mutation
• How it works
  • Each creature is born with some combination of traits; it may not be possible to simply figure out what combination works best for the environment of the creatures.
  • Creatures do their best to reproduce and to survive.
  • If a particular trait or combination of traits helps creatures reproduce or live longer, creatures with that trait (those traits) will tend to have more offspring.
  • Creatures pass on (at least some of) their traits to their offspring. In sexual reproduction, they pass on a combination of the parents' traits.
  • The percentage of creatures with the good traits should increase on each generation.
  • There is a small probability that a new creature will end up with some random traits which it did not inherit from its parent(s). In this way new traits or combinations of traits can be tried out in the world.

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Last updated: 3 October 1995
URL: http://www.indiana.edu/~gasser/evolution.html
Comments: gasser@salsa.indiana.edu
Copyright 1995, The Trustees of Indiana University