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An individual-based evolving predator-prey ecosystem simulation using a fuzzy cognitive map as the behavior model

Abstract : This paper presents 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/prey, distance to potential breeding partner, distance to food, energy level), its internal state (e.g., fear, hunger, curiosity) with memory and choosing several possible actions such as evasion, eating or breeding. The FCM of each individual is unique and is the outcome of the evolution process throughout the simulation. The notion of species is also implemented in a way that species emerge from the evolving population of agents. To our knowledge, our system is the only one that allows modeling the 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, average FCM associated to each species, number of 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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Robin Gras, Didier Devaurs, Adrianna Wozniak, Adam Aspinall. An individual-based evolving predator-prey ecosystem simulation using a fuzzy cognitive map as the behavior model. Artificial Life, Massachusetts Institute of Technology Press (MIT Press), 2009, vol. 15, pp. 423-463. ⟨10.1162/artl.2009.Gras.012⟩. ⟨hal-00862372⟩

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