Social competence improves the performance of biomimetic robots leading live fish.
biomimetic robots
robot learning
social competence
Journal
Bioinspiration & biomimetics
ISSN: 1748-3190
Titre abrégé: Bioinspir Biomim
Pays: England
ID NLM: 101292902
Informations de publication
Date de publication:
04 05 2023
04 05 2023
Historique:
received:
04
11
2022
accepted:
04
04
2023
medline:
2
5
2023
pubmed:
5
4
2023
entrez:
4
4
2023
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 37015241
doi: 10.1088/1748-3190/acca59
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Creative Commons Attribution license.