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Parallel evolution of game evaluation functions in ada

Published:04 November 2007Publication History

ABSTRACT

This is an Ada experience report, where we conclude that Ada tasking and distributed processing facilities make it a good research tool for experimentation with algorithms that might eventually need multiple processors. We implemented a genetic algorithm in Ada to create effective computer players for Connect4. Key to our success was employing Ada tasking and ALRM Annex E Distributed computing to harness a symmetric multiproces-sor and a distributed machine with very few code changes. Easy extension of an original single-task code to multi-tasking and distributed variants-even though extension was not planned in advance-was essential to timely completion. Using either the parallel or distributed implementation, about 150 processor hours were sufficient to evolve players that neither the GNU "Four-in-a-Row" Expert player nor the author could defeat. This algorithm relies on human expertise to restrict the genetic search space. Work is in progress on a new algorithm with near-zero encoded knowledge, which will run on 220 distributed nodes within the same distributed computing framework.

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    • Published in

      cover image ACM Conferences
      SIGAda '07: Proceedings of the 2007 ACM international conference on SIGAda annual international conference
      November 2007
      116 pages
      ISBN:9781595938763
      DOI:10.1145/1315580
      • cover image ACM SIGAda Ada Letters
        ACM SIGAda Ada Letters  Volume XXVII, Issue 3
        SIGAda '07
        December 2007
        93 pages
        ISSN:1094-3641
        DOI:10.1145/1315607
        Issue’s Table of Contents

      Copyright © 2007 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 4 November 2007

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