GP-Gammon: Genetically Programming Backgammon Players

  • Authors:
  • Yaniv Azaria;Moshe Sipper

  • Affiliations:
  • Department of Computer Science, Ben-Gurion University, Beer-Sheva, Israel 84105;Department of Computer Science, Ben-Gurion University, Beer-Sheva, Israel 84105

  • Venue:
  • Genetic Programming and Evolvable Machines
  • Year:
  • 2005

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Abstract

We apply genetic programming to the evolution of strategies for playing the game of backgammon. We explore two different strategies of learning: using a fixed external opponent as teacher, and letting the individuals play against each other. We conclude that the second approach is better and leads to excellent results: Pitted in a 1000-game tournament against a standard benchmark player--Pubeval--our best evolved program wins 62.4% of the games, the highest result to date. Moreover, several other evolved programs attain win percentages not far behind the champion, evidencing the repeatability of our approach.