Agent-Based Modeling
Agent-Based Modeling (ABM) is a computational method used to simulate interactions of individual entities, or "agents," in a system. Each agent acts based on specific rules and behaviors, allowing researchers to observe how local interactions can lead to complex outcomes at a larger scale. ABM is useful in fields like economics, ecology, and social sciences, helping to explore scenarios and predict trends by visualizing how individuals, groups, or components affect one another over time. By modeling these interactions, we gain insights into the dynamics of complex systems, making it a powerful tool for analysis and decision-making.
Additional Insights
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Agent-based modeling (ABM) is a computational method used to simulate the actions and interactions of individual entities, known as agents, within a system. Each agent operates based on its own set of rules, behaviors, and goals, which can mimic real-world decision-making. By observing how these agents interact, researchers can explore complex phenomena, such as human behavior, market trends, or ecological dynamics. ABM helps in understanding how individual choices can lead to collective outcomes, making it a valuable tool in fields like social sciences, economics, and environmental studies.