Sunday, September 14, 2008

Evolving Fish Swimming Through Simulated Evolution

Great story about a robot tuna which has its parameters set up by a genetic algorithm. See the link below:

MIT Ocean Engineering - RoboTuna.

It reminds me of an earlier post here:

Evolving Design Through Simulated Evolution.

An excerpt from the robot tuna case:

"The third and final phase is a search for the optimum swimming performance obtainable within the physical limits imposed by the design of the RoboTuna and the length of the existing testing tank. The current analytical intractability of the fluid dynamics of this problem indicated that the most pragmatic way to proceed would be to optimize the body wave controller experimentally. In simple terms, given the seven parameters which control the swimming body wave, this can be thought of as an experimental search through seven dimentional space. This large number of dimensions quickly creates a massive logistics problem (about 282,475,249 combinations of parameters).

Given that it takes approximately 5 minutes to make a single experimental run down the tank, it would take a time frame in the order of millions of years to perform a blind search through all the combinatorial possiblities in the persuit of an optimum (it is no coincidence that this is about the same amount of time it took for the biological tuna to evolve to its present form). Obviously a more efficient search mechanism is needed, in orger to find the optimum before either time ran out or the apparatus failed mechanically. After a survey of many existing multidimensional space search techniques, a robust, seft-optimizing system based on a Genetic Algorithm was developed."

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