General

• Term: 2017/18 Term 2
• Lecture Time: Thursday, 12:00 - 15:15
• Instructor: Assoc. Prof. Shih-Fen Cheng

Overview

In this course, we introduce agent-based modeling and simulation (ABMS) as an approach for studying complex business and social processes. With examples from domains such as transportation, economics, finance, and urban planning, we show how ABMS can help us better understand complex business and social phenomena. ABMS systems are particularly powerful if we want to describe a system populated by many independent and heterogeneous decision makers (who can be collaborators or competitors). ABMS systems can also be used in performing policy evaluations and generating decision supports, as we can then computationally test how changes in parameters at different levels would affect various performance indicators.

Besides covering theoretic foundations of ABMS, we focus heavily on hands-on learning as well. In particular, we will expose students to NetLogo, an intuitive yet powerful modeling language for building ABMS systems. We will be learning NetLogo by building several classical ABMS examples incrementally in class.

Objective

• Understand what is an ABMS.
• Evaluate the pros and cons of using an ABMS system in describing selected real-world phenomena.
• Utilize ABMS systems in policy/strategy evaluations.
• Appreciate the importance of considering uncertainty and opponent modeling when designing strategic, tactic, and operational policies.
• Complete the full cycle of building an ABMS system using the NetLogo programming language:
• Design an ABMS system with proper level of granularity and fidelity (defining agents and means of communications).
• Validate and calibrate the built ABMS.
• Interpret the outcome of the ABMS system.

Reference Text

• An Introduction to Agent-Based Modeling, by Uri Wilensky and William Rand. The MIT Press, 2015.
  On SMU Library Course Reserve: http://search.library.smu.edu.sg/SMU:Everything:SMU_ALMA2153259750002601

Assessment

Course Schedule