So what is the ‘stochadex’ project?

It’s a simulation engine written in Go which can be used to sample from, and learn computational models for, a whole ‘Pokédex’ of possible real-world systems.

For software engineers, the stochadex simulation framework abstracts away many of the common features that sampling algorithms have for performing these computations behind a highly-configurable interface.

While the concept of a ‘generalised simulation engine’ isn’t new (see, e.g., SimPy, StoSpa, FLAME GPU and loads more), this simulation engine is designed based on deep research into simulating a wide variety of real world systems over many years and has a structure which allows for a lot of cool applications.

What can you do with this software?

One of the most compelling uses for simulation engines is to empower decision-making technologies.

In other words, if you want to answer questions like ‘if I take this action, then what will happen in my system?’, then it is often essential to build a simulation of your system and use this to simulate what might happen in the future.

The stochadex can be used to create these simulations and ensure that they behave in a way with closely matches the real data for the system that they are supposed to be modeling.

Other projects using the software

• Event-based rugby match simulations to evaluate manager decision-making
• Inferring simulations of stock market data for backtesting portfolios
• Fish ecosystem simulations using environment data to evaluate sustanability policies
• Data-driven simulations for UK woodland health monitoring and forecasting
• Decision-making games for the python programmer