Core
The three basic interface of mushroom_rl are the Agent, the Environment and the Core interface.
The
Agentis the basic interface for any Reinforcement Learning algorithm.The
Environmentis the basic interface for every problem/task that the agent should solve.The
Coreis a class used to control the interaction between an agent and an environment.
We provide the logging functionality with the Logger class. Finally, the MushroomObject interface implements
serialization of MushroomRL data on the disk (load/save functionality), forwards a logger down the object tree, and
names its objects through the name and full_name methods.
The data collected while the agent interacts with the environment is stored in a Dataset, and the array type used
to store it is selected per component through the backend declared in MDPInfo and in the agent constructor;
ArrayBackend implements the conversions between them.
This class implements the functions to manage the agent (e.g. move the agent following its policy). |
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Basic interface used by any MushroomRL environment. |
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This class is used to store the information of the environment. |
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Basic interface used by any MushroomRL vectorized environment. |
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Basic interface to run in parallel multiple copies of the same environment. |
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Implements the functions to run a generic algorithm. |
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Collection of the transitions gathered while an agent interacts with an environment. |
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A class to collect and parse step information. |
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Object in charge of assembling the per-timestep context fed to the policy, i.e. the stacked window of the most recent entries of one or more streams. |
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Interface for the array backends used across MushroomRL. |
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Interface to implement serialization and logging of a MushroomRL object. |
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This class implements functions to manage continuous states and action spaces. |
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This class implements functions to manage discrete states and action spaces. |
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This class implements the logging functionality. |