Hill Climbing: Coevolution of Close Relatives

A second experiment attempts learning by coevolution and hill-climbing. An initially blank player is slightly mutated and plays a tournament with these `descendants'. The winner becomes the father of a new generation.

An evolutionary path is thus started. But this method is incapable here of the success it achieves on other domains. The reason is that being better than a close relative gives no information at all on the performance against radically different strategies.

Whereas having an absolute fitness function would allow this incremental methods to climb towards a good solution, Tron has a complex landscape where successful strategies can differ a lot from each other.

This family evolution can climb one of these peaks, but will never get to compare with distant configurations.

Live and let live: An individual is
evolving through small mutations. The
hill-climbing algorithm does not find
general strategies. Instead, the
player in this picture will have a
long life, provided that the other is
doing the same

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