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User Guide

  • Installation
  • About
  • Tutorials

API

  • Agents
  • Environments
  • Core
  • Utilities
  • Trainers
  • Common
GenRL
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  • Welcome to GenRL’s documentation!
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Welcome to GenRL’s documentation!¶

Features¶

  • Unified Trainer and Logging class: code reusability and high-level UI
  • Ready-made algorithm implementations: ready-made implementations of popular RL algorithms.
  • Extensive Benchmarking
  • Environment implementations
  • Heavy Encapsulation useful for new algorithms

Contents¶

User Guide

  • Installation
    • PyPI Package
    • From Source
  • About
    • Introduction
    • Policies and Values
    • Trainers and Loggers
    • Agent Encapsulation
    • Environments
  • Tutorials
    • Bandit Tutorials
    • Classical
    • Deep RL Tutorials
    • Custom Policy Networks
    • Using A2C
    • Using Shared Parameters in Actor Critic Agents in GenRL
    • Vanilla Policy Gradient (VPG)
    • Saving and Loading Weights and Hyperparameters with GenRL

API

  • Agents
    • A2C
    • DDPG
    • DQN
    • PPO1
    • VPG
    • TD3
    • SAC
    • Q-Learning
    • SARSA
    • Contextual Bandit
    • Multi-Armed Bandit
  • Environments
    • Environments
    • Vectorized Envrionments
  • Core
    • ActorCritic
    • Base
    • Buffers
    • Noise
    • Policies
    • RolloutStorage
    • Values
  • Utilities
    • Logger
    • Utilities
    • Models
  • Trainers
    • On-Policy Trainer
    • Off-Policy Trainer
    • Classical Trainer
    • Deep Contextual Bandit Trainer
    • Multi Armed Bandit Trainer
    • Base Trainer
  • Common
    • Classical Common
    • Bandit Common
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© Copyright 2020, Society for Artificial Intelligence and Deep Learning (SAiDL) Revision ce767e43.

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