Agent-Based Simulation Overview

This seminar provides a comprehensive discussion of agent-based simulation (ABS), which has been the “hottest” topic in simulation modeling since 2005. In an ABS autonomous agents (people, vehicles, organizations, etc.), which have attributes and potentially complex behaviors, interact with each other and their environment over time.

ABS has been successfully applied to a diverse set of problems (defense, supply chains, evacuation of crowds, epidemiology, market behavior, traffic flows, sociology, etc.), and improved software packages, faster computers, and multi-core processors have facilitated model development and analysis. However, learning ABS on one’s own is difficult, at best, due to the genuine lack of clarity and consistency in the literature. Much of the confusion is due to the literal “smokescreen” of characteristics that are often associated with ABS, including autonomy, agents interacting with other other and their environment, time stepping, learning, adaptation, simple behavioral rules defined “locally,” emergence, bottom-up modeling, and complex adaptive systems. Based on 10 years of extensive research, we discuss what we believe to be the real essence of ABS. Many so-called fundamental tenets of ABS such as time stepping and emergence are shown to not be required. The seminar includes 12 videos of ABS in action. Technical support is provided by e-mail. The course length corresponds to that of a one-day live seminar. Live versions of this seminar have been presented many times, including onsite seminars for Caterpillar and the U.S. Navy.

“The Agent-Based Simulation online course is excellent. I highly recommend this course to anyone interested in ABS. I am new to ABS and it was a perfect introduction for me. I could not have gotten up to speed with the concepts this quickly without it.”  Robin Clark, Operations Research Analyst, QMT Group

Outline

What You Will Learn (look to the right for more detail):

  1. The True Nature of Agents and Agent-Based Simulation
  2. Relationship with Discrete-Event Simulation
  3. Historical Perspective Including Three Classical Models
  4. Software for Agent-Based Simulation
  5. Development and Analysis of Five Agent-Based Simulation Models
  6. Successful Applications of Agent-Based Simulation