2023-07-25 –, 32-144
Integrated Assessment Models (IAMs) are scientific models which enable the evaluation of the social and economic impact of environmental policies. WorldDynamics.jl is an open-source package that allows the development and reproduction of modern and historical IAMs in Julia. In this workshop, we demonstrate the main functionalities of the package while guiding the audience with comprehensive hands-on examples.
Integrated Assessment Models (IAMs) are valuable tools for a broad range of fields, including Economics and Social Science, enabling the evaluation of the economic and social impact of various environmental policies. They rely on scientific computing to analyze and understand complex and dynamic systems. We present WorldDynamics.jl, an open-source Julia package that allows the development and reproduction of IAMs using modern scientific computing techniques. In this workshop, we are going to interactively demonstrate the main functionalities of WorldDynamics.jl to the Julia community while guiding the audience with comprehensive hands-on examples.
Currently, the package reproduces the whole family of system dynamics models, from Jay Forrester's WORLD1 to the recent Earth4All, including the notable WORLD3, which was reimplemented directly from the DYNAMO code to Julia. Using the ModelingToolkit structure, each model is treated as a collection of subsystems, which are self-contained ODESytem with their own parameters, variables, and equations. All subsystems are connected into a single system, which forms the complete model, with interactions represented as a system of differential equations and solved using DifferentialEquations.jl and ModelingToolkit.jl. This modular structure allows us to play with subsystems individually and combine them in different ways into a unique model with little effort. Besides the original models, it is also straightforward to add existing updated versions as an extension, which exemplifies how a user is able to create their own update from a well-known model.
In this workshop, we are going to present the package functionalities with hands-on examples using several of the currently available models. Initially, we start with a general explanation of the package, emphasizing how it is being developed. Subsequently, we proceed with the major demonstration of the package's main features via practical coding cases, including the reproduction of the original figures from implemented historical models using PlotJS.jl. We also show how to alter the values of parameters, tables, and edit equations of models, leveraging the package modular approach to combine different subsystems in ways that were not easily achievable previously. Finally, we present the development roadmap, which includes current works under construction, our expectations for the near future, and what we intend to achieve in the next major releases.
After the workshop, we expect the audience will be able to have a clear comprehension of current WorldDynamics.jl capabilities and functionalities. Along with this talk, we are also submitting a talk proposal to present the motivation and goals behind the package, to share the model development process, and the challenges we face.
Paulo Bruno Serafim is a Ph.D. student in Computer Science at the Gran Sasso Science Institute. His research interests include scientific machine learning applied to Integrated Assessment Models and neural network optimization. Furthermore, he develops work in multi-agent cooperation and competition, emulation of human play styles in Non-Player Characters, and interpretability of autonomous agents using Deep Reinforcement Learning techniques. In the past, he worked as a Research Engineer at the COATI team at the Centre Inria d'Université Côte d'Azur, as well as a Lead Data Scientist, Computer Vision Engineer, and Computer Graphics Engineer at the Instituto Atlântico. He holds a Master's degree and a Magna Cum Laude Bachelor's degree in Computer Science from the Federal University of Ceara, where he is an external collaborator of the CRAb research group.