An Evolutionary Strategies Toolkit for high speed blackbox optimization. Evokit currently supports Classic ES (p, λ), Natural Evolutionary Strategies, and Canonical Evolutionary Strategies optimization. It requires a processor supporting AVX operations.
This toolkit has two binaries:
evo-rank
: an out of the box ES ranker similar to the papers listed belowmulberry
: a framework that supports custom optimization goals, including market level metrics. As most of our work is focused on this framework, the readme outlines this.Please see docs/DEVELOPMENT.md for how to run this code locally and edit the code in this repo.
In the above flowchart you can see a high level view of how Mulberry learns a new model.
A user must provide:
For a more detailed view on each component of Mulberry, please see docs/MULBERRY.md. You can also see more information in the cargo docs.
To build your own pipeline using Mulberry, please see docs/BUILDING_PIPELINE.md.