Robofish as Social Partner for Live
Guppies
Lea Musiolek
1(B) , Verena V. Hafner
1 , Jens Krause
2 , Tim Landgraf
3 ,
and David Bierbach
2
1 Department of Computer Science, Humboldt-Universit¨ at zu Berlin,
Berlin, Germany
lea.musiolek@hu-berlin.de
2 Faculty of Life Sciences, Division of Biology and Ecology of Fishes,
Humboldt Universit¨ at zu Berlin, Berlin, Germany
3 Dahlem Center for Machine Learning and Robotics, Freie Universit¨ at Berlin,
Berlin, Germany
https://adapt.informatik.hu-berlin.de/
https://www.agrar.hu-berlin.de/
http://berlinbiorobotics.blog/
Abstract. Biomimetic robots that are accepted as social partners by
animals may help to gain insights into animals’ social interaction skills.
Here, we present an experiment using the biomimetic Robofish which
resembles live guppies (Poecilia reticulata) - a small tropical freshwater
fish. Guppy females were given the opportunity to interact with different
open-loop controlled Robofish replicas. We show that guppies interacting
with a lifelike Robofish replica scored higher on social interaction variables than did those faced with a simple white cuboid performing the
same movements, although this effect weakened with time. Our study
exemplifies the use of Robofish as a research tool, providing highly standardized social cues for the study of fish social skills such as imitation
and following.
Keywords: Biorobotics · Fish · Social interaction.
1 Introduction
When equipping artificial agents with social interaction skills such as imitation,
following and anticipation of others’ movements [6], it makes sense to examine
how animals implement and exploit such skills in their social interactions [4].
Some major issues when using live animals as social stimuli (social partners)
are (I) consistent individual behavioural differences even between demonstrator
animals, and (II) inevitable mutual influences between the focal and demonstrator animals. Here, the use of biomimetic robots is a promising solution.
Biomimetic robots can be either interactive (closed-loop behaviour) or static
Supported by Germany’s Excellence Strategy - EXC 2002/1 “Science of Intelligence”.
c
Springer Nature Switzerland AG 2020
V. Vouloutsi et al. (Eds.): Living Machines 2020, LNAI 12413, pp. 270–274, 2020.
https://doi.org/10.1007/978-3-030-64313-3_26
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