Abstract

Group behaviours in fish are widespread, and are increasingly used to develop new optimisation algorithms for solving complex tasks. However, how external factors regulate individual spatial location in a fish school represents an overlooked aspect that is fundamental to understand collective dynamics. Herein, the neon tetra Paracheirodon innesi , a highly social fish species, has been used to analyse the effect of different ecological contexts, including food availability and predation risk, on the place preference of individual agents in the group. A robotic school of fish has been developed to establish a biohybrid interaction enabling accurate isolation of the individual choice of living fish without disturbance from other conspecifics. Results show that the individual optimal position in the group is context dependent, as individual fish continuously modify their location in the school according to different external scenarios. Individual fish stayed as close to food as possible to better compete with conspecifics. In the presence of a robotic predator, fish preferred to locate in the middle of the aggregation to favour dilution effects. When no stimuli were provided, fish preferred to stay at the back of the school, probably to exploit the increased likelihood of predator detection by conspecifics swimming ahead. This study provides new basic knowledge on how swarm intelligence and self-organisation processes of fish are affected by the individual agent. Furthermore, these findings can inspire innovative task optimisation approaches potentially applicable in engineering contexts. • Fish aggregations are self-organised systems affected by several external factors. • Individual place preference in fish aggregations is a fundamental aspect to unveil. • A robotic school of fish replicas has been developed to interact with neon tetras. • Individual fish behaviour in the school was modulated by different external stimuli. • These findings can inspire new meta-heuristic approaches for task optimisation.

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