Relevant information as a formalised approach to evaluate game mechanics

Christoph Salge; T. Mahlmann

doi:10.1109/ITW.2010.5593344

Relevant information as a formalised approach to evaluate game mechanics

Christoph Salge, T. Mahlmann

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

12 Citations (Scopus)

51 Downloads (Pure)

Abstract

We present a new approach to use adaptive AI in the game design process to aid evaluating of game mechanics. During production, this is a crucial task to improve the player satisfaction with a game title. The problem with automated game evaluation via AI is the measurement of values that indicate the quality of the game mechanics. We apply the Information Theory based concept of “Relevant Information” to this problem and argue that there is a relation between enjoyment related gameplay properties and Relevant Information. We also demonstrate, with a simple game implementation, how an adaptive AI can be used to approximate the Relevant Information, and how those measurable numerical values related to certain game design flaws.

Original language	English
Title of host publication	Procs of IEEE Symposium on Computational Intelligence and Games
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	281-288
ISBN (Electronic)	978-1-4244-6296-4
ISBN (Print)	978-1-4244-6295-7
DOIs	https://doi.org/10.1109/ITW.2010.5593344
Publication status	Published - 2010

Keywords

Al and games
information theory
game development
strategic games

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10.1109/ITW.2010.5593344

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“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”
Accepted author manuscript, 1.82 MB

Cite this

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title = "Relevant information as a formalised approach to evaluate game mechanics",

abstract = "We present a new approach to use adaptive AI in the game design process to aid evaluating of game mechanics. During production, this is a crucial task to improve the player satisfaction with a game title. The problem with automated game evaluation via AI is the measurement of values that indicate the quality of the game mechanics. We apply the Information Theory based concept of “Relevant Information” to this problem and argue that there is a relation between enjoyment related gameplay properties and Relevant Information. We also demonstrate, with a simple game implementation, how an adaptive AI can be used to approximate the Relevant Information, and how those measurable numerical values related to certain game design flaws.",

keywords = "Al and games, information theory, game development, strategic games",

author = "Christoph Salge and T. Mahlmann",

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year = "2010",

doi = "10.1109/ITW.2010.5593344",

language = "English",

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AU - Salge, Christoph

AU - Mahlmann, T.

N1 - “This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”

PY - 2010

Y1 - 2010

N2 - We present a new approach to use adaptive AI in the game design process to aid evaluating of game mechanics. During production, this is a crucial task to improve the player satisfaction with a game title. The problem with automated game evaluation via AI is the measurement of values that indicate the quality of the game mechanics. We apply the Information Theory based concept of “Relevant Information” to this problem and argue that there is a relation between enjoyment related gameplay properties and Relevant Information. We also demonstrate, with a simple game implementation, how an adaptive AI can be used to approximate the Relevant Information, and how those measurable numerical values related to certain game design flaws.

AB - We present a new approach to use adaptive AI in the game design process to aid evaluating of game mechanics. During production, this is a crucial task to improve the player satisfaction with a game title. The problem with automated game evaluation via AI is the measurement of values that indicate the quality of the game mechanics. We apply the Information Theory based concept of “Relevant Information” to this problem and argue that there is a relation between enjoyment related gameplay properties and Relevant Information. We also demonstrate, with a simple game implementation, how an adaptive AI can be used to approximate the Relevant Information, and how those measurable numerical values related to certain game design flaws.

KW - Al and games

KW - information theory

KW - game development

KW - strategic games

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DO - 10.1109/ITW.2010.5593344

M3 - Conference contribution

AN - SCOPUS:80051939901

SN - 978-1-4244-6295-7

SP - 281

EP - 288

BT - Procs of IEEE Symposium on Computational Intelligence and Games

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

Relevant information as a formalised approach to evaluate game mechanics

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Keywords

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