SimpleDistributedRL
Contents
Installation
How To Use
Distributed Learning (Online)
Custom
Making a Custom environment
Making a Custom algorithm
Detailed Framework
API
EnvConfig
RLConfig
RLConfig Parameters
Runner(Base)
Runner
Algorithms
Q-Learning
Deep Q-Networks
Rainbow
Agent57
Agent57 light
PPO(Proximal Policy Optimization)
DDPG(Deep Deterministic Policy Gradient)
SAC(Soft-Actor-Critic)
SND(Self-supervised Network Distillation)
Monte Carlo tree search
AlphaZero
MuZero
DreamerV3
SimpleDistributedRL
Welcome to SimpleDistributedRL's documentation!
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Welcome to SimpleDistributedRL's documentation!
Contents
Installation
Install options
必須ライブラリ
その他のライブラリ
How To Use
1. EnvConfig
2. RLConfig
3. Runner
4. Runner functions
Distributed Learning (Online)
0. 必要なライブラリのインストール
1. Redisサーバの起動
2. TrainerServer/ActorServerの起動
3. 学習の実施
Custom
Making a Custom environment
1. 環境クラスの実装
2. Spaceクラスについて
3. 自作環境の登録
4. 実装例
5. Q学習による学習例
Making a Custom algorithm
1. 概要
2. 実装する各クラスの説明
3. 自作アルゴリズムの登録
4. 型ヒント
5. 実装例(Q学習)
Detailed Framework
Overview
Play flow
Multiplay flow
Class diagram
Interface Type
API
EnvConfig
EnvConfig
RLConfig
RLConfig
RLConfig Parameters
Memory
RLConfigComponentFramework
InputValueBlock
InputImageBlock
MLPBlock
DuelingNetwork
Scheduler
LRSchaduler
Runner(Base)
RunnerBase
Runner
Runner
Algorithms
Q-Learning
Config
Deep Q-Networks
Config
Rainbow
Config
Agent57
Config
Agent57 light
Config
PPO(Proximal Policy Optimization)
Config
DDPG(Deep Deterministic Policy Gradient)
Config
SAC(Soft-Actor-Critic)
Config
SND(Self-supervised Network Distillation)
Config
Monte Carlo tree search
Config
AlphaZero
Config
MuZero
Config
DreamerV3
Config
Indices and tables
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モジュール索引
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