Crate border_core
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Core components for reinforcement learning.
Modules
Errors in the library.
Types for recording various values obtained during training and evaluation.
A generic implementation of replay buffer.
Utilities for interaction of agents and environments.
Macros
Structs
All information given at every step of agent-envieronment interaction.
Manages training loop and related objects.
Configuration of Trainer.
Traits
A set of actions of the environment.
Represents a trainable policy on an environment.
A batch of samples.
Represents an environment, typically an MDP.
Additional information to Obs
and Act
.
A set of observations of an environment.
A policy on an environment.
Interface of replay buffers.
Shape of observation or action.
Process Step and output an item.