SLM Lab
v4.2.0
v4.2.0
  • SLM Lab
  • 🖥Setup
    • Installation
    • Quick Start
  • 🚀Using SLM Lab
    • Lab Command
    • Lab Organization
    • Train: REINFORCE CartPole
    • Resume and Enjoy: REINFORCE CartPole
    • Agent Spec: DDQN+PER on LunarLander
    • Env Spec: A2C on Pong
    • GPU Usage: PPO on Pong
    • Parallelizing Training: Async SAC on Humanoid
    • Experiment and Search Spec: PPO on Breakout
    • Run Benchmark: A2C on Atari Games
    • Meta Spec: High Level Specifications
    • Post-Hoc Analysis
    • TensorBoard: Visualizing Models and Actions
    • Using SLM Lab In Your Project
  • 📈Analyzing Results
    • Data Locations
    • Graphs and Data
    • Performance Metrics
  • 🥇Benchmark Results
    • Public Benchmark Data
    • Discrete Environment Benchmark
    • Continuous Environment Benchmark
    • Atari Environment Benchmark
    • RL GIFs
  • 🔧Development
    • Modular Design
      • Algorithm Taxonomy
      • Class Inheritance: A2C > PPO
    • Algorithm
      • DQN
      • REINFORCE
      • Actor Critic
    • Memory
      • Replay
      • PrioritizedReplay
      • OnPolicyReplay
      • OnPolicyBatchReplay
    • Net
      • MLP
      • CNN
      • RNN
    • Profiling SLM Lab
  • 📖Publications and Talks
    • Book: Foundations of Deep Reinforcement Learning
    • Talks and Presentations
  • 🤓Resources
    • Deep RL Resources
    • Contributing
    • Motivation
    • Help
    • Contact
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  1. 🥇Benchmark Results

RL GIFs

A collection of replay GIFs generated from SLM Lab agents in "enjoy" mode.

ppo beamrider

ppo breakout

BeamRider

Breakout

ppo kungfumaster

ppo mspacman

KungFuMaster

MsPacman

ppo pong

ppo qbert

Pong

Qbert

ppo seaquest

ppo spaceinvaders

Seaquest

SpaceInvaders

sac ant

sac halfcheetah

Ant

HalfCheetah

sac hopper

sac humanoid

Hopper

Humanoid

sac doublependulum

sac pendulum

Inv.DoublePendulum

InvertedPendulum

sac reacher

sac walker

Reacher

Walker

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Last updated 5 years ago

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