Agent-based model

An agent-based model (ABM) is a computational model for simulating the actions and interactions of an autonomous agent to understand the behavior of a system and what governs its outcomes. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo methods are used to understand the stochasticity of these models. Particularly within ecology, an ABM is also called an individual-based model (IBM). A review of literature on individual-based models, agent-based models, and multiagent systems shows that ABMs are used in many scientific domains including biology, ecology, and social science. Agent-based modeling is related to, but distinct from, the concept of a multi-agent system.