Participant selection strategy for collaboration in multi-agent intelligent health monitoring systems

Xiaoli Zhang M.D.; Senlin Yang M.D.; Bianlian Zhang M.D.; Hao Li M.D.

doi:10.1117/12.2551431

31 January 2020 Participant selection strategy for collaboration in multi-agent intelligent health monitoring systems

Xiaoli Zhang M.D., Senlin Yang M.D., Bianlian Zhang M.D., Hao Li M.D.

Proceedings Volume 11427, Second Target Recognition and Artificial Intelligence Summit Forum; 114271B (2020) https://doi.org/10.1117/12.2551431
Event: Second Target Recognition and Artificial Intelligence Summit Forum, 2019, Changchun, China

Abstract

In multi-agent systems, agents coordinate their behavior and work together to achieve a shared goal through collaboration. However, in multi-agent systems, selecting qualified participants to form effective collaboration communities is challenging. In this paper, we propose a minimum circle covering algorithm, as a solution for on-demand participant selection for collaboration in multi-agent systems. Furthermore, a twenty-one point FBG sensors are divided into four sensing function agent in Structural Health Monitoring (SHM) system is experimented in an aircraft wing box. Correspondingly, there are four intelligent evaluation agents and one system collaborative agent in the multi-agent intelligent health monitoring system. For the damage loading position prediction on the aircraft wing box, the collaborative participation selection strategy based on the minimum circle coverage is verified experimentally. The research result indicates that the minimum circle covering algorithm can be used to select the participation in multi-agent intelligent health monitoring system, of all the participations in the collaboration, it enables them to identify and select a qualified participants.

Citation Download Citation

Xiaoli Zhang M.D., Senlin Yang M.D., Bianlian Zhang M.D., and Hao Li M.D. "Participant selection strategy for collaboration in multi-agent intelligent health monitoring systems", Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114271B (31 January 2020); https://doi.org/10.1117/12.2551431

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