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Paranoid algorithm

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Algorithm in game theory

In combinatorial game theory, the paranoid algorithm is an algorithm that aims to improve the alpha-beta pruning capabilities of the max algorithm by making the player p chosen to maximize the score "paranoid" of the other players by assuming they are cooperating to minimize p's score, thus minimizing any n-player game to a two-player game by making the opposing player the sum of the other player's scores. This returns the game to a zero-sum game and makes it analyzable via any optimization techniques usually applied in pair with the minimax theorem. It performs notably faster than the max algorithm because of those optimizations.

See also

References

  1. Sturtevant, Nathan; Korf, Richard (30 July 2000). "On Pruning Techniques for Multi-Player Games" (PDF). AAAI-00 Proceedings: 201–207.
  2. Sturtevant, Nathan (2003). "A Comparison of Algorithms for Multi-player Games". Lecture Notes in Computer Science. Vol. 2883. Berlin, Heidelberg: Springer Berlin Heidelberg. pp. 108–122. doi:10.1007/978-3-540-40031-8_8. ISBN 978-3-540-20545-6.
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