An individual-based evolving predator-prey ecosystem simulation using a fuzzy cognitive map as the behavior model
Gras, Robin and Devaurs, Didier and Wozniak, Adrianna and Aspinall, Adam (2009) An individual-based evolving predator-prey ecosystem simulation using a fuzzy cognitive map as the behavior model. Artificial Life, 15 (4). pp. 423-463. ISSN 1530-9185 (https://doi.org/10.1162/artl.2009.Gras.012)
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Abstract
We present an individual-based predator-prey model with, for the first time, each agent behavior being modeled by a fuzzy cognitive map (FCM), allowing the evolution of the agent behavior through the epochs of the simulation. The FCM enables the agent to evaluate its environment (e.g., distance to predator or prey, distance to potential breeding partner, distance to food, energy level) and its internal states (e.g., fear, hunger, curiosity), and to choose several possible actions such as evasion, eating, or breeding. The FCM of each individual is unique and is the result of the evolutionary process. The notion of species is also implemented in such a way that species emerge from the evolving population of agents. To our knowledge, our system is the only one that allows the modeling of links between behavior patterns and speciation. The simulation produces a lot of data, including number of individuals, level of energy by individual, choice of action, age of the individuals, and average FCM associated with each species. This study investigates patterns of macroevolutionary processes, such as the emergence of species in a simulated ecosystem, and proposes a general framework for the study of specific ecological problems such as invasive species and species diversity patterns. We present promising results showing coherent behaviors of the whole simulation with the emergence of strong correlation patterns also observed in existing ecosystems.
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Item type: Article ID code: 90261 Dates: DateEvent1 October 2009PublishedNotes: © 2009 Massachusetts Institute of Technology Subjects: Science > Mathematics > Electronic computers. Computer science
Science > Natural history > Biology
Science > ZoologyDepartment: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 15 Aug 2024 10:42 Last modified: 15 Aug 2024 10:42 URI: https://strathprints.strath.ac.uk/id/eprint/90261