pytorchrl
stable

Getting started:

  • Motivation
  • Installation

PyTorchRL API:

  • Agent Components
    • Actors
      • Off-Policy Actor
      • On-Policy Actor
      • Model-Based Actor
      • Actor Components
        • Action prob. distributions
        • Feature Extractors
        • Memory Networks
        • Noise
        • Reward Functions
        • World Models
    • Algorithms
    • Available Environments
    • Environment Vectors
    • Storage
  • Training Components

Tutorials:

  • Breaking down PyTorchRL
  • Create a custom environment

Code examples:

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

Actors

  • Off-Policy Actor
  • On-Policy Actor
  • Model-Based Actor

Actor Components

  • Action prob. distributions
    • Categorical
    • Gaussian
    • Squashed Gaussian
  • Feature Extractors
    • Multilayer Perceptron (MLP)
    • Convolutional Neural Network (CNN)
    • Residual CNN with Fixup initialization (Fixup)
    • Multimodal Neural Network (DictNet)
  • Memory Networks
    • Gated Recurrent Unit (GRU)
  • Noise
    • Gaussian Noise
    • Ornstein-Uhlenbeck Noise
  • Reward Functions
    • Gym CartPole
    • Gym Pendulum
    • MuJoCO Inverted Pendulum
    • MuJoCo HalfCheetah
    • PyBullet HalfCheetah
  • World Models
    • WorldModel
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