An agent-based model of an endangered population of the Arctic fox from Mednyi Island

• Main Authors: Brilliantova, Angelina, Pletenev, Anton, Doronina, Liliya, Hosseini, Hadi
• Format: Report
• Language: unknown
• Published: arXiv 2018
• Subjects: Multiagent Systems cs.MA; Artificial Intelligence cs.AI; Populations and Evolution q-bio.PE; FOS Computer and information sciences; FOS Biological sciences; Arctic; Arctic Fox
• Online Access: https://dx.doi.org/10.48550/arxiv.1807.06103; https://arxiv.org/abs/1807.06103

Artificial Intelligence techniques such as agent-based modeling and probabilistic reasoning have shown promise in modeling complex biological systems and testing ecological hypotheses through simulation. We develop an agent-based model of Arctic foxes from Medniy Island while utilizing Probabilistic Graphical Models to capture the conditional dependencies between the random variables. Such models provide valuable insights in analyzing factors behind catastrophic degradation of this population and in revealing evolutionary mechanisms of its persistence in high-density environment. Using empirical data from studies in Medniy Island, we create a realistic model of Arctic foxes as agents, and study their survival and population dynamics under a variety of conditions. : The AI for Wildlife Conservation (AIWC) Workshop at IJCAI 2018