Agent Based Modeling and Simulation

Welcome to the course of Agent Based Modeling and Simulation (ABMS) . The course intends to explore the use of learning techniques in ABMS. For this, traditional ABMS, as developed using NetLogo, is introduced in detail. Then, the use of Machine Learning techniques in this context, i.e., supervised and reinforcement learning, is briefly reviewed. The organization of the course is as follows:

Introduction | abms-syllabus

1. Agent Based Modeling and Simulation | 1; 3:1 | abms-slides-01
2. Getting Started with NetLogo | 1; 3:2 | abms-slides-02
3. The ODD Protocol | 1:3 | abms-slides-03
4. Implementing a First Agent Based Model | 1:4 | abms-slides-04
5. From Animation to Science | 1:5 | abms-slides-05
6. Testing your Programs | 1:6 | abms-slides-06
7. Emergence | 1:8 | abms-slides-07
8. Stochasticity | 1:15 | abms-slides-08
9. Collectives | 1:16 |abms-slides-09
10. Patterns for Model Structure | 1:17-18 | abms-slides-10
11. Patterns for Theory Development | 1:19 | abms-slides-11
12. Analyzing and Understanding ABMs | 1:22 |
13. Introduction to Reinforcement Learning | 2:1 |
14. Finite Markov Decision Processes  | 2:3 |
15. Temporal-Difference Learning | 2:6 |
16. Weka and NetLogo |

X:Y stands for reference X, chapter Y.

Ligas

1. Guía de estilo en NetLogo | URL

References

1. S. F. Railsback and V. Grimm. Agent-Based and Individual-Based Modeling. Princeton University Press, Princeton, New Jersey, USA, 2019.
2. R. Sutton and A. G. Barto. Reinforcement Learning: An Introduction. MIT Press, Cambridge, MA., USA, 2018.
3. U. Wilensky and W. Rand. An introduction to agent-based modeling: modeling natural, social, and engineered complex systems with NetLogo. MIT Press, Cambridge, MA., USA, 2015.