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

Journal: Bioinspiration & biomimetics
PMID:

Abstract

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.

Authors

  • Moritz Maxeiner
    Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.
  • Mathis Hocke
    Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.
  • Hauke J Moenck
    Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.
  • Gregor H W Gebhardt
    Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.
  • Nils Weimar
    Department of Biology and Ecology of Fishes, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany.
  • Lea Musiolek
    Excellence Cluster 'Science of Intelligence', Technische Universität Berlin, 10587 Berlin, Germany.
  • Jens Krause
  • David Bierbach
  • Tim Landgraf
    Freie Universität Berlin, FB Mathematik u. Informatik Arnimallee 7, 14195 Berlin, Germany.