Literature DB >> 26934093

Population and Evolutionary Dynamics based on Predator-Prey Relationships in a 3D Physical Simulation.

Takashi Ito, Marcin L Pilat, Reiji Suzuki, Takaya Arita1.   

Abstract

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.

Keywords:  3D virtual physical environment; Virtual creatures; eco-evolutionary feedback; morphology–behavior coevolution; population and evolutionary dynamics; predator–prey coevolution

Mesh:

Year:  2016        PMID: 26934093     DOI: 10.1162/ARTL_a_00201

Source DB:  PubMed          Journal:  Artif Life        ISSN: 1064-5462            Impact factor:   0.667


  1 in total

1.  Deep-Reinforcement Learning-Based Co-Evolution in a Predator-Prey System.

Authors:  Xueting Wang; Jun Cheng; Lei Wang
Journal:  Entropy (Basel)       Date:  2019-08-08       Impact factor: 2.524

  1 in total

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