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2016-10-01

Pathfinding via genetic algorithms

Pathfinding via genetic algorithms

The problem we want to solve is to get from a starting point to a goal point avoiding obstacles.

NOTE. There are many efficient, ad-hoc algorithms (e.g. A*) that should be preferred for real pathfinding tasks, but this is a good example of the flexibility of GA.

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(There's also a related question / answer on Stackoverflow)

Posted by Manlio Morini at 19:08 No comments:
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Labels: genetic algorithms, path finding, tutorial, vita
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