pytorchrl
stable

Getting started:

  • Motivation
  • Installation

PyTorchRL API:

  • Agent Components
    • Actors
    • Algorithms
    • Available Environments
    • Environment Vectors
    • Storage
      • Off-policy
      • On-Policy
      • Model-Based
  • Training Components

Tutorials:

  • Breaking down PyTorchRL
  • Create a custom environment

Code examples:

  • Simplified Code Examples
  • Unity 3D Obstacle Tower Environment
pytorchrl
  • »
  • Agent Components »
  • Storage
  • Edit on GitHub

Storage

  • Off-policy
    • Replay buffer
    • N-Step Replay Buffer
    • Prioritized Experience Replay Buffer
    • Emphasizing Recent Experience Replay Buffer (ERE)
    • Hindsight experience replay buffer (HER)
  • On-Policy
    • Vanilla On-Policy Buffer
    • Generalized Advantage Estimator (GAE) Buffer
    • V-trace Buffer
    • Proximal Policy Optimization with Demonstrations Buffer (PPOD)
  • Model-Based
    • ModelBased Replay Buffer
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