Agent-Based Modeling (ABM)
Definition
A computational approach for simulating the actions and interactions of autonomous agents to evaluate their effects on the system as a whole.
Role: It provides the overall simulation in which agents interact.
The Problem That Led to It
A real system may contain thousands or millions of individuals whose actions influence one another. Studying only the overall system can hide how individual behavior creates that outcome.
What Problem It Solves
ABM allows us to model:
Individual agents ↓ Their actions ↓ Their interactions ↓ Collective/system-level effects
What Happens If Not Used
We may understand the overall result but have difficulty understanding how individual actions and interactions produced it.
Easy Wording
ABM is a simulation where many agents interact so we can study what happens to the whole system.
Layman Example
Imagine a marketplace with hundreds of shoppers.
Each shopper makes individual purchasing decisions.
Together, those decisions affect:
- demand
- prices
- availability
Technical Example
Environment ↓ Agent A ──┐ Agent B ──┼── interact Agent C ──┘ ↓ Individual actions ↓ Collective effects ↓ System behavior
Limitation
The more agents, behaviors, and interactions we model, the more complicated the simulation becomes.
Solution
To make agents behave differently, we need to define who each agent is initially.
That is the Agent Profile.
