Lim, S;
Bentley, P;
(2019)
All in Good Team: Optimising Team Personalities for Different Dynamic Problems and Task Types.
In:
ALIFE 2019: Proceedings of the Artificial Life Conference.
(pp. pp. 153-160).
MIT Press
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Abstract
Change is inevitable in this fast-moving world. As the environment and people’s needs continuously change, so must the project. In our previous work, we developed an agent-based model of human collaboration that incorporates individual personalities. In this work, we applied a genetic algorithm to select the optimal personality combinations of a team in order to cope with different types of project change. We studied change in the context of three types of tasks: disjunctive (team performance is the performance achieved by the best performing individual), conjunctive (team performance is the performance achieved by the worst performing individual), and additive (team performance is the total performance of the group). Results reveal that different compositions of team personalities are suitable for different dynamic problems and task types. In particular, optimal personalities found for static problems differ from optimal personalities found for dynamic problems.
| Type: | Proceedings paper |
|---|---|
| Title: | All in Good Team: Optimising Team Personalities for Different Dynamic Problems and Task Types |
| Event: | ALIFE 2019: The 2019 Conference on Artificial Life |
| Location: | Newcastle, UK |
| Dates: | 29 July 2019 - 02 August 2019 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1162/isal_a_00155 |
| Publisher version: | https://doi.org/10.1162/isal_a_00155 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10078225 |
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