GP-gammon: Using genetic programming to evolve backgammon players

Yaniv Azaria; Moshe Sipper

doi:10.1007/978-3-540-31989-4_12

GP-gammon: Using genetic programming to evolve backgammon players

Yaniv Azaria
, Moshe Sipper

Research output: Contribution to journal › Conference article › peer-review

21 Scopus citations

Abstract

We apply genetic programming to the evolution of strategies for playing the game of backgammon. Pitted in a 1000-game tournament against a standard benchmark player - Pubeval - our best evolved program wins 58% of the games, the highest verifiable result to date. Moreover, several other evolved programs attain win percentages not far behind the champion, evidencing the repeatability of our approach.

Original language	English
Pages (from-to)	132-142
Number of pages	11
Journal	Lecture Notes in Computer Science
Volume	3447
DOIs	https://doi.org/10.1007/978-3-540-31989-4_12
State	Published - 1 Jan 2005
Event	8th European Conference on Genetic Programming, EuroGP 2005 - Lausanne, Switzerland Duration: 30 Mar 2005 → 1 Apr 2005

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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10.1007/978-3-540-31989-4_12

Cite this

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title = "GP-gammon: Using genetic programming to evolve backgammon players",

abstract = "We apply genetic programming to the evolution of strategies for playing the game of backgammon. Pitted in a 1000-game tournament against a standard benchmark player - Pubeval - our best evolved program wins 58\% of the games, the highest verifiable result to date. Moreover, several other evolved programs attain win percentages not far behind the champion, evidencing the repeatability of our approach.",

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AU - Sipper, Moshe

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N2 - We apply genetic programming to the evolution of strategies for playing the game of backgammon. Pitted in a 1000-game tournament against a standard benchmark player - Pubeval - our best evolved program wins 58% of the games, the highest verifiable result to date. Moreover, several other evolved programs attain win percentages not far behind the champion, evidencing the repeatability of our approach.

AB - We apply genetic programming to the evolution of strategies for playing the game of backgammon. Pitted in a 1000-game tournament against a standard benchmark player - Pubeval - our best evolved program wins 58% of the games, the highest verifiable result to date. Moreover, several other evolved programs attain win percentages not far behind the champion, evidencing the repeatability of our approach.

UR - https://www.scopus.com/pages/publications/24644444707

U2 - 10.1007/978-3-540-31989-4_12

DO - 10.1007/978-3-540-31989-4_12

M3 - Conference article

AN - SCOPUS:24644444707

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JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

Y2 - 30 March 2005 through 1 April 2005

ER -

GP-gammon: Using genetic programming to evolve backgammon players

Abstract

ASJC Scopus subject areas

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