Optimizing the efficiency of collective decision making in groups

Turalska, Malgorzata, Lickorish, Rosie, De Mel, Geeth, Turner, Liam ORCID: https://orcid.org/0000-0003-4877-5289 and Whitaker, Roger ORCID: https://orcid.org/0000-0002-8473-1913 2021. Optimizing the efficiency of collective decision making in groups. Presented at: SPIE Defense + Commercial Sensing, Virtual (FL, United States), 12-14 April 2021. Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III. , vol.11746 International Society for Optics and Photonics, 10.1117/12.2587886

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Abstract

The complexity of modern military operations create a demand for efficient collaborative decision making and problem solving. Additionally, as military units operate in increasingly dynamic environments, the ability to respond to changing circumstances becomes paramount for mission success. An effective response rests on correct dissemination and transfer of information across the command and control structure, and thus is critically linked to the network of human interactions. In this paper, we take an agent-based modeling approach to collective problem solving. We investigate three key factors affecting the performance in collaborative environments: (1) the structure of network used to share information between agents, (2) the search strategies adopted by agents, and (3) the complexity of problems facing the group. In particular we study how the trade-off between exploitation of known solutions and exploration for novel ones is related to the efficiency of collective search. Additionally we consider the role of agent behavior: propensity for risk-taking and trustworthiness, as well as the dynamic nature of social connections. Finally, we outline the directions for future work regarding the efficiency of problem solving on military-like command and control structures.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics Crime and Security Research Institute (CSURI)
Publisher:	International Society for Optics and Photonics
Date of First Compliant Deposit:	7 July 2021
Date of Acceptance:	18 December 2020
Last Modified:	28 Apr 2023 06:26
URI:	https://orca.cardiff.ac.uk/id/eprint/142394

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