The features in MushroomRL are 1-D arrays computed applying a specified function to a raw input, e.g. polynomial features of the state of an MDP. MushroomRL supports three types of features:
- basis functions;
- tensor basis functions;
- tiles.
The tensor basis functions are a PyTorch implementation of the standard basis functions. They are less straightforward than the standard ones, but they are faster to compute as they can exploit parallel computing, e.g. GPU-acceleration and multi-core systems.
All the types of features are exposed by a single factory method Features that builds the one requested by the user.
mushroom_rl.features.features
The factory method returns a class that extends the abstract class FeatureImplementation.
mushroom_rl.features._implementations.features_implementation
The documentation for every feature type can be found here:
features/mushroom_rl.features.basis features/mushroom_rl.features.tensors features/mushroom_rl.features.tiles