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Studying Animal Swarms May Help Us Improve Smart Technology

Recent research shows that fish can accurately forecast the actions of others and incorporate it into their own actions

Holden Galusha

Holden Galusha is the associate editor for Lab Manager. He was a freelance contributing writer for Lab Manager before being invited to join the team full-time. Previously, he was the...

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A study published in August as an accepted manuscript on the website of the Bioinspiration and Biomimetrics journal provides deeper insight into the mechanisms behind the behavior of fish swimming in shoals. These findings may deepen our understanding of biological intelligence and prove valuable to the development of more intelligent, socially competent robots.

Shoals of fish, as opposed to schools, are less coordinated and may consist of fish from various species. However, the individual fishes of both shoals and schools display remarkable coordination and anticipatory behavior. Biologist David Bierbach of Humboldt University and his research team aimed to shed light on the mechanisms enabling this behavior. The researchers built a robotic fish that guppies accepted as a conspecific and programmed it to swim in the same zig-zag pattern across the fish tank three times. The guppies exhibited anticipatory behavior at both “global” and “local” levels, which the researchers defined as “the relative time until the robot fish reached its final position” and “the timing and location of the live fish’s turns in relation to robofish turns,” respectively.

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Global anticipatory behavior was displayed when the guppies successfully anticipated the robot fish’s destination, with more than half of the guppies reaching the destination before the robot fish did. Local anticipation was demonstrated across the trials as the guppies incrementally improved their timing to mirror the robot fish, eventually making the same turn shortly before the robotic fish did. This observation shows that the fish were able to improve their behavior forecasting and act accordingly.

Ideally, the insight gleaned from this research will further our understanding of animals’ social competence that facilitates anticipatory behaviors. These processes could then be replicated in smart intelligence technology, such as robots that can accurately forecast what a human is going to do and act accordingly to help them with their task.