University of Sussex
Browse
2015-Fodor-Agents and Avatars Event Based Analysis-ACCEPTED.pdf (309.14 kB)

Agents and avatars: event based analysis of competitive differences

Download (309.14 kB)
conference contribution
posted on 2023-06-09, 14:29 authored by Mikael Fodor, Pejman Mirza-Babaei, Judith Good
Investigations into playing against computer and human controlled opponents have shown higher levels of arousal against human opponents. Most experiments however measure this by using post play surveys. In contrast, the study reported in this paper used physiological measurements to allow for different events during competitive play to be analysed. Twenty participants played two death matches in Call of Duty: Black Ops 2. Although participants played against an agent in both matches, participants were told that they were playing against an agent in one match, and an avatar in the other. Significant differences in participants' arousal level were found when the enemy was first encountered, though measures became more mixed as the interactions played out. The believability of the avatar may have influenced the results, as not all participants seemed convinced of the humanity of the AI. Overall, the experimental results can form a basis for further investigation into this area.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

Proceedings of the 2015 Annual Symposium on Computer-Human Interaction in Play

Publisher

Association for Computing Machinery

Page range

511-516

Event name

CHI Play 2015 The ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play

Event location

London, UK

Event type

conference

Event date

October 3-5, 2015

ISBN

9781450334662

Department affiliated with

  • Informatics Publications

Research groups affiliated with

  • Creative Technology Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2018-08-13

First Open Access (FOA) Date

2018-08-13

First Compliant Deposit (FCD) Date

2018-08-09

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC