General Video Game Evaluation Using Relative Algorithm Performance Profiles

Thorbjørn Nielsen; Gabriella Barros; Julian Togelius; Mark Nelson

doi:10.1007/978-3-319-16549-3_30

General Video Game Evaluation Using Relative Algorithm Performance Profiles

Thorbjørn Nielsen, Gabriella Barros, Julian Togelius, Mark Nelson

Center for Digital Play

Publikation: Konference artikel i Proceeding eller bog/rapport kapitel › Konferencebidrag i proceedings › Forskning › peer review

Abstract

In order to generate complete games through evolution we need generic and reliably evaluation functions for games. It has been suggested that game quality could be characterised through playing a game with different controllers and comparing their performance. This paper explores that idea through investigating the relative performance of different general game-playing algorithms. Seven game-playing algorithms was used to play several hand-designed, mutated and randomly generated VGDL game descriptions. Results discussed appear to support the conjecture that well-designed games have, in average, a higher performance difference between better and worse game-playing algorithms.

Originalsprog	Engelsk
Titel	Applications of Evolutionary Computation : 18th European Conference, EvoApplications 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings
Antal sider	12
Forlag	Springer Publishing Company
Publikationsdato	2015
Sider	369-380
ISBN (Trykt)	978-3-319-16548-6
ISBN (Elektronisk)	978-3-319-16549-3
DOI	https://doi.org/10.1007/978-3-319-16549-3_30
Status	Udgivet - 2015
Begivenhed	Evostar 2015: EvoGAMES - Bio-inspired Algorithms in Games - http://www.evostar.org/2015/cfp_evogames.php, Copenhagen, Danmark Varighed: 8 apr. 2015 → 10 apr. 2015 http://www.evostar.org/2015/cfp_evogames.php

Konference

Konference	Evostar 2015
Lokation	http://www.evostar.org/2015/cfp_evogames.php
Land/Område	Danmark
By	Copenhagen
Periode	08/04/2015 → 10/04/2015
Internetadresse	http://www.evostar.org/2015/cfp_evogames.php

Navn	Lecture Notes in Computer Science
Vol/bind	9028
ISSN	0302-9743

Emneord

Game quality assessment
General game-playing algorithms
Evolutionary game generation
VGDL
Performance difference analysis

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10.1007/978-3-319-16549-3_30

Nielsen2015GeneralAccepteret manuskript, 259 KB

Citationsformater

Nielsen, Thorbjørn ; Barros, Gabriella ; Togelius, Julian et al. / General Video Game Evaluation Using Relative Algorithm Performance Profiles. Applications of Evolutionary Computation: 18th European Conference, EvoApplications 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings. Springer Publishing Company, 2015. s. 369-380 (Lecture Notes in Computer Science, Bind 9028).

@inproceedings{24700217918946c8b7826dd02f4887e7,

title = "General Video Game Evaluation Using Relative Algorithm Performance Profiles",

abstract = "In order to generate complete games through evolution we need generic and reliably evaluation functions for games. It has been suggested that game quality could be characterised through playing a game with different controllers and comparing their performance. This paper explores that idea through investigating the relative performance of different general game-playing algorithms. Seven game-playing algorithms was used to play several hand-designed, mutated and randomly generated VGDL game descriptions. Results discussed appear to support the conjecture that well-designed games have, in average, a higher performance difference between better and worse game-playing algorithms.",

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year = "2015",

doi = "10.1007/978-3-319-16549-3_30",

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booktitle = "Applications of Evolutionary Computation",

address = "United States",

note = "Evostar 2015 : EvoGAMES - Bio-inspired Algorithms in Games ; Conference date: 08-04-2015 Through 10-04-2015",

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}

Nielsen, T, Barros, G, Togelius, J & Nelson, M 2015, General Video Game Evaluation Using Relative Algorithm Performance Profiles. i Applications of Evolutionary Computation: 18th European Conference, EvoApplications 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings. Springer Publishing Company, Lecture Notes in Computer Science, bind 9028, s. 369-380, Evostar 2015, Copenhagen, Danmark, 08/04/2015. https://doi.org/10.1007/978-3-319-16549-3_30

General Video Game Evaluation Using Relative Algorithm Performance Profiles. / Nielsen, Thorbjørn; Barros, Gabriella; Togelius, Julian et al.
Applications of Evolutionary Computation: 18th European Conference, EvoApplications 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings. Springer Publishing Company, 2015. s. 369-380 (Lecture Notes in Computer Science, Bind 9028).

Publikation: Konference artikel i Proceeding eller bog/rapport kapitel › Konferencebidrag i proceedings › Forskning › peer review

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N2 - In order to generate complete games through evolution we need generic and reliably evaluation functions for games. It has been suggested that game quality could be characterised through playing a game with different controllers and comparing their performance. This paper explores that idea through investigating the relative performance of different general game-playing algorithms. Seven game-playing algorithms was used to play several hand-designed, mutated and randomly generated VGDL game descriptions. Results discussed appear to support the conjecture that well-designed games have, in average, a higher performance difference between better and worse game-playing algorithms.

AB - In order to generate complete games through evolution we need generic and reliably evaluation functions for games. It has been suggested that game quality could be characterised through playing a game with different controllers and comparing their performance. This paper explores that idea through investigating the relative performance of different general game-playing algorithms. Seven game-playing algorithms was used to play several hand-designed, mutated and randomly generated VGDL game descriptions. Results discussed appear to support the conjecture that well-designed games have, in average, a higher performance difference between better and worse game-playing algorithms.

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KW - General game-playing algorithms

KW - Evolutionary game generation

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KW - Performance difference analysis

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Nielsen T, Barros G, Togelius J, Nelson M. General Video Game Evaluation Using Relative Algorithm Performance Profiles. I Applications of Evolutionary Computation: 18th European Conference, EvoApplications 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings. Springer Publishing Company. 2015. s. 369-380. (Lecture Notes in Computer Science, Bind 9028). doi: 10.1007/978-3-319-16549-3_30

General Video Game Evaluation Using Relative Algorithm Performance Profiles

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