Explore agent-based modeling and its applications in social sciences through this comprehensive lecture by Bill Rand. Learn about emergence, non-linear effects, and the benefits of appropriate representation in complex systems. Discover when to use agent-based modeling (ABM), its advantages over other modeling approaches, and its various uses including description, explanation, experimentation, and prediction. Gain insights into the limitations and resistance to ABM, as well as its potential for education, communication, and thought experiments. Delve into concepts like heterogeneity, local interactions, adaptation, and the connection between complex systems, ABM, and psychohistory.
Overview
Syllabus
Introduction to NetLogo by Bill Rand
Model 1: Example of Emergence - Traffic
Model 2
Model 3: Non - Linear Effect
Model 4
Representation
Benefits of Appropriate Representation
Representation of Complex Systems
A Third Way of Doing Science
Integrative Understanding
Differential Understanding
Why ABM and When to Use It?
When to use ABM?
Medium Numbers
Heterogeneity
Complex but Local Interactions
Rich Environments
Time
Adaptation
Agent-Based Modeling ABM vs. Equation-Based Modeling EBM
ABM and Statistical Modeling
ABM vs. Lab Experiments
ABM vs. Aggregate Computer Modeling
Limitations
Why the Resistance?
Uses of ABM
Description
Explanation
Experimentation
Analogy
Education / Communication
Touchstone
Thought Experiments
Prediction
Complex Systems, Agent-Based Modeling and Psychohistory
Taught by
International Centre for Theoretical Sciences
