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Proceedings Paper

Effect of cooperative team size on coordination in adaptive multi-agent systems
Author(s): D. E. Asher; S. L. Barton; E. Zaroukian; N. R. Waytowich
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Paper Abstract

In recent work, we utilized convergent cross mapping (CCM) to quantify coordination in a multi-agent reinforcement learning (MARL) paradigm by measuring causal influence between pairs of agents in a joint task. CCM was originally developed to detect causal influences within ecological systems, and as we previously demonstrated, it can be used to measure causal dependencies between pairs of time-series data. While this work has provided important insight into the coordination between 2 teammates, it is not clear how such coordination scales with the number of agents working together with a shared goal. Within a predator-prey pursuit environment, the current study investigates the influence that an incremental increase in number of predator agents has on the inherently causal relationship between predators working together to pursue a single prey. We hypothesize that averaged CCM values will decrease with increasing number of predators due to a redistribution of coordination across all predator agents. This work provides a quantitative assessment for the fundamental influence that number of cooperative agents has on the causal relationship between agents working together on a joint task, and insight into coordinated group behaviors.

Paper Details

Date Published: 10 May 2019
PDF: 12 pages
Proc. SPIE 11006, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, 110060Z (10 May 2019); doi: 10.1117/12.2518626
Show Author Affiliations
D. E. Asher, U.S. Army Research Lab. (United States)
S. L. Barton, U.S. Army Research Lab. (United States)
E. Zaroukian, U.S. Army Research Lab. (United States)
N. R. Waytowich, U.S. Army Research Lab. (United States)

Published in SPIE Proceedings Vol. 11006:
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications
Tien Pham, Editor(s)

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