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Artificial Life and Intelligent Agents Symposium

ALIA 2016: Artificial Life and Intelligent Agents pp 117–129Cite as

Identifying Human-Like Qualities for Non-player Characters

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 732))

Abstract

This research investigates qualities common to non-player characters in games can contribute towards an in-game agents believability. A number of NPCs with different initial setups were evaluated using a blind Turing Test style evaluation, in which players were pitted against another human and different AI controlled NPCs over six rounds. At the end of each round, players were asked to rate both opponents, unknowing which was human or NPC. The results demonstrated that none of the agents were able to reliably fool the player, however, some combinations of characteristics were successful in generating behaviour that was perceived as ‘human-like’.

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Author information

Authors and Affiliations

  1. University of Lincoln, Lincolnshire, England, UK

    Jason A. Hall & Christopher J. Headleand

  2. Bangor University, Gwynedd, Wales, UK

    Llyr Ap Cenydd

Authors
  1. Jason A. Hall
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  2. Llyr Ap Cenydd
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  3. Christopher J. Headleand
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Corresponding author

Correspondence to Jason A. Hall .

Editor information

Editors and Affiliations

  1. Aston Lab for Intelligent Collectives Engineering (ALICE), Aston University, Birmingham, United Kingdom

    Peter R. Lewis

  2. Computer Science Department, Lincoln University, Lincoln, United Kingdom

    Christopher J. Headleand

  3. Department of Computer Science and Creative Technologies, University of the West of England, Bristol, United Kingdom

    Steve Battle

  4. School of Computer Science, Bangor University, Bangor, United Kingdom

    Panagiotis D. Ritsos

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Hall, J.A., Cenydd, L.A., Headleand, C.J. (2018). Identifying Human-Like Qualities for Non-player Characters. In: Lewis, P., Headleand, C., Battle, S., Ritsos, P. (eds) Artificial Life and Intelligent Agents. ALIA 2016. Communications in Computer and Information Science, vol 732. Springer, Cham. https://doi.org/10.1007/978-3-319-90418-4_10

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  • DOI: https://doi.org/10.1007/978-3-319-90418-4_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-90417-7

  • Online ISBN: 978-3-319-90418-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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