AbstractionsΒΆ

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PARL aims to build an agent for training algorithms to perform complex tasks.
The main abstractions introduced by PARL that are used to build an agent recursively are the following:
  • Model is abstracted to construct the forward network which defines a policy network or critic network given state as input.
  • Algorithm describes the mechanism to update parameters in the model and often contains at least one model.
  • Agent, a data bridge between the environment and the algorithm, is responsible for data I/O with the outside environment and describes data preprocessing before feeding data into the training process.

Note: For more information about base classes, please visit our tutorial and API document.