research-article

Strategy Games: The Components of A Worthy Opponent

Authors:

Richard BartleAuthors Info & Claims

FDG '20: Proceedings of the 15th International Conference on the Foundations of Digital Games

Article No.: 48, Pages 1 - 9

https://doi.org/10.1145/3402942.3403018

Published: 17 September 2020 Publication History

Abstract

What distinguishes a good AI opponent from a bad one in the eyes of players? To answer this question, hundreds of opinions were analysed, as expressed by strategy-game players in forums; from these, a grounded theory was formed. It was found that the AI’s role as an opponent in a game shapes player expectations, and that not breaking these is instrumental to players’ enjoyment. The expectations include: keeping a tension between the player and AI; maintaining a level playing field; and more subtle expectations involving closure and the ability to rectify behaviour. The nature of these expectations are explored, as well as how they might be upheld.

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Cited By

Zhu JVillareale JJavvaji NRisi SLöwe MWeigelt RHarteveld CKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)Player-AI Interaction: What Neural Network Games Reveal About AI as PlayProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445307(1-17)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445307

Strategy Games: The Components of A Worthy Opponent

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Published In

cover image ACM Other conferences

FDG '20: Proceedings of the 15th International Conference on the Foundations of Digital Games

September 2020

804 pages

ISBN:9781450388078

DOI:10.1145/3402942

Editors:
Georgios N. Yannakakis
University of Malta
,
Antonios Liapis
University of Malta
,
Penny Kyburz
Australian National University
,
Vanessa Volz
Modl.AI
,
Foaad Khosmood
California Polytechnic State University
,
Phil Lopes
École Polytechnique Fédèrale de Lausanne

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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New York, NY, United States

Publication History

Published: 17 September 2020

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IGGI EPSRC Centre for Doctoral Training

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FDG '20

FDG '20: International Conference on the Foundations of Digital Games

September 15 - 18, 2020

Bugibba, Malta

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Cited By

Zhu JVillareale JJavvaji NRisi SLöwe MWeigelt RHarteveld CKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)Player-AI Interaction: What Neural Network Games Reveal About AI as PlayProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445307(1-17)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445307

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