An Accurate Induction Method Of Player Ratings From Tournament Results
Maire, Frederic D. & Rasmussen, Rune K. (2004) An Accurate Induction Method Of Player Ratings From Tournament Results. In Simulated Evolution And Learning (SEAL04), October 26 – 29, 2004, BEXCO, Busan, Korea,.
![[img]](http://eprints.qut.edu.au/style/images/fileicons/application_pdf.png)
Abstract
Competitive co-evolution has been successfully applied to breed artificial players. The fitness of players is evaluated through competition with other players. The estimation of
the fitness (rating) of players is the computational bottleneck of this approach. It is therefore desirable to exploit as best as possible the information contained in the outcomes of played games. In this paper, we introduce an efficient induction method of player ratings from tournament results. We demonstrate empirically that the proposed formula gives more accurate results than the estimation formula that is traditionally
used.
Citations:
Citation countsare sourced monthly from Scopus and Web of Science citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science generally from 1980 onwards.
Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads:
Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
| ID Code: | 486 |
|---|---|
| Item Type: | Conference Paper |
| Keywords: | artificial players, player rating, fitness function, tournament, genetic algorithm |
| Subjects: | Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) |
| Divisions: | Past > QUT Faculties & Divisions > Faculty of Science and Technology |
| Copyright Owner: | Copyright 2004 (Please consult author) |
| Deposited On: | 25 Oct 2004 |
| Last Modified: | 29 Feb 2012 23:08 |
Export: EndNote | Dublin Core | BibTeX
Repository Staff Only: item control page