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12 April 2021 Optimizing the efficiency of collective decision making in groups
Malgorzata Turalska, Geeth De Mel, Rosie Lickorish, Liam Turner, Roger M. Whitaker
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Proceedings Volume 11746, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III; 117460L (2021) https://doi.org/10.1117/12.2587886
Event: SPIE Defense + Commercial Sensing, 2021, Online Only
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.
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Malgorzata Turalska, Geeth De Mel, Rosie Lickorish, Liam Turner, and Roger M. Whitaker "Optimizing the efficiency of collective decision making in groups", Proc. SPIE 11746, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III, 117460L (12 April 2021); https://doi.org/10.1117/12.2587886
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