VR For Predator Fish Teaches Us About Behaviour
Researchers from Princeton University have undertaken a novel project in VR: They have created what essentially amounts to a sensory video game for fish to play, in order to tell us more about the thoughts and behaviours predatory fish exhibit when they see the behaviour of potential prey.
In so doing, we learn much more about the predator-prey dynamic, and how to simulate the full thing ourselves. We also learn about how to create robotic 'prey' fish that can go unchallenged in the sea, as they attempt to blend in with their surrounding shoals.
Overall, the VR was more of an augmented reality simulation than a true virtual reality. Due to the nature of the participants, it was not possible to wire them up for truly artificial sensory stimulation, and given our incomplete models of underwater environments, detrimental to do so in the first place. So, the user fish - the famously ravenous bluegill sunfish were placed in a tank, and the simulated prey fish projected onto the far wall of the tank with a standard projector display system. The key was to project in such a manner as the virtual fish appeared to be inside the ttank as opposed to outside of it.
The researchers, led by Iain Couzin, an assistant professor of ecology and evolutionary biology at Princeton who studies collective animal behaviour, created an evolvable simulation in this manner, with the prey fish's numbers, and behaviour under their control. It allowed them, using the physical predators, to observe how group formation and movement alone protect against predatory attack.
The simulation tracked in real time the positions of the physical fish, and used this to control the relative movements of the prey. The prey interacted spontaneously with one another based on encoded behaviour traits, and the researchers documented in the prey the resulting individual behaviour and group formations as they interacted with the physical predators. In the end, they discovered something surprising: the bluegills were most likely to avoid attacking simulated prey that had formed coordinated and mobile groups.
This research has produced some of the strongest direct evidence that collective motion in animal groups such as schools of fish can evolve as a finely tuned defence against attack from predators.
These results show that group formation itself can dissuade a predator, even if the prey as in the simulation are completely unaware of the danger, the researchers report. This suggests that the specific configuration of animal groups is an evolved defence in its own right, Couzin explained. The ideal configurations exhibited by the simulated prey mirror those of many animal groups, wherein individuals follow cues from their near-neighbours to coordinate collective movement.
"This sort of hybrid virtual approach has given us a way of tapping into these long-lasting questions that have really evaded standard analysis for decades," Couzin said.
"To conduct this type of study is very intensive in terms of statistics and creating control models of what predators would have done, given the prey that were available to them in that particular situation at that time and compare that to the behaviour of the real behaviour," Couzin said. "And that's one of the reasons why these studies have been so difficult in the past using classic experimental means."
An important aspect of the simulation is that it let the researchers control the behavior of individual prey, Couzin said. In nature, animals can respond to a predator in different and unpredictable ways animals might react as the predator approaches or after the initial attack. In addition, group cohesion depends on the number of animals assembled and environmental factors such as terrain.
For the Princeton study, the researchers encoded each individual prey with various strengths of three traits a tendency to be attracted to, swim in the same direction as, or ignore nearby individuals. Thus, individual prey would either swim alone, group together, or follow other prey, or exhibit a combination of traits.