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Evolving strategy for a probabilistic game of imperfect information using genetic programming

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Abstract

We provide the complete record of methodology that let us evolve BrilliAnt, the winner of the Ant Wars contest. Ant Wars contestants are virtual ants collecting food on a grid board in the presence of a competing ant. BrilliAnt has been evolved through a competitive one-population coevolution using genetic programming and fitnessless selection. In this paper, we detail the evolutionary setup that lead to BrilliAnt’s emergence, assess its direct and indirect human-competitiveness, and describe the behavioral patterns observed in its strategy.

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Notes

  1. The Ing Foundation stopped to funding the prize in 2000.

  2. We considered using a single tree and mapping the diagonal board views into the straight ones; however, this leads to significant topological distortions which could deteriorate ant’s perception.

  3. We estimate the statistical significance of the outcome of a match from the tails of the binomial distribution assuming the probability of success of .5 (the zero hypothesis is that both players win the same number of games, i.e., 50,000 games in this context).

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Acknowledgments

The authors wish to thank the anonymous reviewers for valuable feedback and discussion on this work. This research has been supported by the Ministry of Science and Higher Education grant # N N519 3505 33.

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Correspondence to Krzysztof Krawiec.

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Jaśkowski, W., Krawiec, K. & Wieloch, B. Evolving strategy for a probabilistic game of imperfect information using genetic programming. Genet Program Evolvable Mach 9, 281–294 (2008). https://doi.org/10.1007/s10710-008-9062-1

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