Social competence improves the performance of biomimetic robots leading live fish.

Autor:	Maxeiner M; Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany., Hocke M; Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany., Moenck HJ; Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany., Gebhardt GHW; Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.; Computational Systems Neuroscience, Institute of Zoology, University of Cologne, Cologne, Germany., Weimar N; Institute of Zoology, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany., Musiolek L; Department of Computer Science, Humboldt-Universität zu Berlin, Berlin, Germany.; Cluster of Excellence 'Science of Intelligence', Technical University of Berlin, Marchstrasse 23, 10587 Berlin, Germany., Krause J; Faculty of Life Sciences, Albrecht Daniel Thaer Institute of Agricultural and Horticultural Sciences, Humboldt Universität zu Berlin, Berlin, Germany.; Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany.; Cluster of Excellence 'Science of Intelligence', Technical University of Berlin, Marchstrasse 23, 10587 Berlin, Germany., Bierbach D; Faculty of Life Sciences, Albrecht Daniel Thaer Institute of Agricultural and Horticultural Sciences, Humboldt Universität zu Berlin, Berlin, Germany.; Cluster of Excellence 'Science of Intelligence', Technical University of Berlin, Marchstrasse 23, 10587 Berlin, Germany., Landgraf T; Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.; Cluster of Excellence 'Science of Intelligence', Technical University of Berlin, Marchstrasse 23, 10587 Berlin, Germany.
Jazyk:	angličtina
Zdroj:	Bioinspiration & biomimetics [Bioinspir Biomim] 2023 May 04; Vol. 18 (4). Date of Electronic Publication: 2023 May 04.
DOI:	10.1088/1748-3190/acca59
Abstrakt:	Collective motion is commonly modeled with static interaction rules between agents. Substantial empirical evidence indicates, however, that animals may adapt their interaction rules depending on a variety of factors and social contexts. Here, we hypothesized that leadership performance is linked to the leader's responsiveness to the follower's actions and we predicted that a leader is followed longer if it adapts to the follower's avoidance movements. We tested this prediction with live guppies that interacted with a biomimetic robotic fish programmed to act as a 'socially competent' leader. Fish that were avoiding the robot were approached more carefully in future approaches. In two separate experiments we then asked how the leadership performance of the socially competent robot leader differed to that of a robot leader that either approached all fish in the same, non-responsive, way or one that did change its approach behavior randomly, irrespective of the fish's actions. We found that (1) behavioral variability itself appears attractive and that socially competent robots are better leaders which (2) require fewer approach attempts to (3) elicit longer average following behavior than non-competent agents. This work provides evidence that social responsiveness to avoidance reactions plays a role in the social dynamics of guppies. We showcase how social responsiveness can be modeled and tested directly embedded in a living animal model using adaptive, interactive robots. (Creative Commons Attribution license.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu