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Learning from Ants

Published on 1/31/2011

Could stronger go-playing programs draw their inspiration from ants? A recent article in the Journal of Experimental Biology showed that Argentinian ants were able to solve a maze generated by the Tower of Hanoi mathematical puzzle, working together to optimally find their way to food, and researchers hope that computerized optimization algorithms can adopt the ant’s biological algorithm. Israeli go player Shavit Fragman, in turn, wonders “What can we learn from biological systems to solve the go maze?” Seeking to bridge the gap between the Towers of Hanoi and solving a life and death problem, Shavit offers a challenge to “translate a tsumego into a problem of finding the shortest path in a maze and program an algorithm mimicking the ant’s behavior to find the solution.” Click here to read more about this.

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Learning from Ants

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