Given a model of a complex system, cadCAD can simulate the impact that a set of actions might have on it. This helps users make informed, rigorously tested decisions on how best to modify or interact with the system in order to achieve their goals.
cadCAD supports different system modeling approaches and can be easily integrated with common empirical data science workflows. Monte Carlo methods, A/B testing and parameter sweeping features are natively supported and optimized for.
cadCAD (complex adaptive dynamics Computer-Aided Design) is a python based modeling framework for research, validation, and Computer Aided Design of complex systems.
cadCAD helps you answer the "what if" questions about your system
Account for uncertainty in your models using Monte Carlo methods to run stochastic simulations
Make different assumptions about agent behavior while keeping the rest of the system constant with A/B testing
Make an informed decision when fine tuning your system with data from a parameter sweeping simulation
What will you ask of your system?
Install cadCAD and read through our documentation and guides. You may also find this community-created list of resources quite helpful too.
In this series of videos, we introduce basic concepts of cadCAD and system modeling in general using a simple toy model.
We've gathered a list of videos and resources to give you some inspiration for the application of cadCAD in your project.
The most comprehensive cadCAD beginner course on the web. If you're new to cadCAD, your journey starts here.
Become the futuristic, solarpunk character in this Commons Simulator adventure to correct the course of history.
cadCAD was created as an internal tool at BlockScience – an engineering, R&D and analytics firm specializing in complex systems design and validation