General Game Heuristic Prediction Based on Ludeme Descriptions

Matthew Stephenson, Dennis J.N.J. Soemers, Éric Piette, Cameron Browne

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

This paper investigates the performance of different general-game-playing heuristics for games in the Ludii general game system. Based on these results, we train several regression learning models to predict the performance of these heuristics based on each game's description file. We also provide a condensed analysis of the games available in Ludii, and the different ludemes that define them.

Original languageEnglish
Title of host publication2021 IEEE Conference on Games (CoG)
PublisherInstitute of Electrical and Electronics Engineers
Pages1-4
Number of pages4
ISBN (Electronic)9781665438865
DOIs
Publication statusPublished - 17 Aug 2021
Externally publishedYes
Event2021 IEEE Conference on Games, CoG 2021 - Copenhagen, Denmark
Duration: 17 Aug 202120 Aug 2021

Publication series

NameIEEE Conference on Computatonal Intelligence and Games, CIG
Volume2021-August
ISSN (Print)2325-4270
ISSN (Electronic)2325-4289

Conference

Conference2021 IEEE Conference on Games, CoG 2021
Country/TerritoryDenmark
CityCopenhagen
Period17/08/2120/08/21

Keywords

  • Data Mining
  • General Game Playing
  • Heuristics
  • Ludemes
  • Ludii
  • Supervised Learning

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