代理人基模型 agent-based model (ABM) , 又称多元代理人系统（multi-agent system, MAS）,　若代理人具有异质性，则称为异质代理人模型（heterogeneous agent model, HAM）, 是一种用来模拟具有自主意识的智能体（独立个体或共同群体，例如组织，团队）的行动和相互作用的计算模型，通过图像展示评估智能体在系统整体中的作用。它综合了一些其他思想，比如博弈论, 复杂系统, 涌现, 计算社会学, 多智能体系统和 演化计算. 采用蒙特卡洛方法产生随机性。

An agent-based model (ABM) is one of a class of computational models for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) with a view to assessing their effects on the system as a whole. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo methods are used to introduce randomness. Particularly within ecology, ABMs are also called individual-based models (IBMs), and individuals within IBMs may be simpler than fully autonomous agents within ABMs. A review of recent literature on individual-based models, agent-based models, and multiagent systems shows that ABMs are used on non-computing related scientific domains including biology, ecology and social science. Agent-based modeling is related to, but distinct from, the concept of multi-agent systems or multi-agent simulation in that the goal of ABM is to search for explanatory insight into the collective behavior of agents obeying simple rules, typically in natural systems, rather than in designing agents or solving specific practical or engineering problems.