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Artificial Life

Spring 2016, Vol. 22, No. 2, Pages 226-240
(doi: 10.1162/ARTL_a_00201)
© 2016 Massachusetts Institute of Technology. Published under a Creative Commons Attribution 3.0 Unported (CC BY 3.0) license.
Population and Evolutionary Dynamics based on Predator–Prey Relationships in a 3D Physical Simulation
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Recent studies have reported that population dynamics and evolutionary dynamics, occurring at different time scales, can be affected by each other. Our purpose is to explore the interaction between population and evolutionary dynamics using an artificial life approach based on a 3D physically simulated environment in the context of predator–prey and morphology–behavior coevolution. The morphologies and behaviors of virtual prey creatures are evolved using a genetic algorithm based on the predation interactions between predators and prey. Both population sizes are also changed, depending on the fitness. We observe two types of cyclic behaviors, corresponding to short-term and long-term dynamics. The former can be interpreted as a simple population dynamics of Lotka–Volterra type. It is shown that the latter cycle is based on the interaction between the changes in the prey strategy against predators and the long-term change in both population sizes, resulting partly from a tradeoff between their defensive success and the cost of defense.