An open-source Python package that assists in the processes of designing, testing and validating complex systems through simulation.
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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
What if I'm not sure about some of my assumptions?
Account for uncertainty in your models using Monte Carlo methods to run stochastic simulations
What if agents that interact with my system behaved differently?
Make different assumptions about agent behavior while keeping the rest of the system constant with A/B testing
What if I changed this parameter?
Make an informed decision when fine tuning your system with data from a parameter sweeping simulation