A library for training reinforcement learning agents. Its philosophy is to separate the RL machinery from the end user, so that users provide an environment and get back a trained agent who can then act intelligently in that environment, whatever it may be.
It is inspired by (and may at some point wrap) https://github.com/aunum/gold, but with the goal of separating out the "internals" of the training, so it is as easy as possible to apply RL to new situations.
Run:
go run examples/main.go
To create your own environment, see pkg/coach/environment.go