Agent-Based Modeling
Agent-Based Modeling (ABM) is a computational simulation methodology where autonomous agents interact within an environment to model complex systems and emergent phenomena. It focuses on individual behaviors and local interactions to understand how macro-level patterns arise from micro-level decisions. ABM is widely used in social sciences, economics, biology, and engineering to study systems like traffic flows, market dynamics, or disease spread.
Developers should learn ABM when building simulations for complex adaptive systems where traditional equation-based models fail, such as in epidemiology, urban planning, or financial markets. It's particularly valuable for scenarios requiring modeling of heterogeneous agents, adaptive behaviors, or network effects, enabling insights into system resilience, policy impacts, or emergent trends through bottom-up analysis.