Abstract

Abstract Demographic models describe population dynamics in terms of the distribution of individuals among categories (e.g., age or size classes); such models are called i-state distribution models . In contrast, i-state configuration models describe population dynamics by simulating the birth, development, and eventual death of each individual in the population. Such models (also referred to, less precisely, as individual-based models ) are necessary when interactions among individuals make the assumptions of i -state distribution models untenable. The basic components of an i -state configuration model are a set of individuals (each characterized by its i -state), an interaction structure, and an environment. Each of these components changes dynamically as a function of the others. The implementation of i -state distribution models is familiar; here we present a general framework, based on object-oriented programming (OOP), for the numerical implementation of i -state configuration models. The individuals, interaction structure, and environment are all defined as objects. A special object called the simulator transfers information among these objects as needed. The properties of OOP (data protection, inheritance, polymophism, modularity) lend themselves naturally to i -state configuration simulations.

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