An agent-based modelling toolkit for various dynamic modelling and simulation. The package is essentially designed for epidemiologists and health economists.
Ordinary Differential Equation models and State-Space Agent-Based models are two major and mature model types supported. PyComplexism also strongly supports the combination of models (hybrid modelling, metapopulation, and multi-scale modelling).
We use
- Bayesian Networks for parameter modelling.
- Contiuous-Time Bayesian Networks and Markov Chain for dynamics of agents' states.
- Monte Carlo and Bayesian inference for post-modelling inference.