SOTAVerified

OpenAI Gym

An open-source toolkit from OpenAI that implements several Reinforcement Learning benchmarks including: classic control, Atari, Robotics and MuJoCo tasks.

(Description by Evolutionary learning of interpretable decision trees)

(Image Credit: OpenAI Gym)

Papers

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Showing 251–300 of 382 papers

TitleStatusHype
Deep Q-Network Based Multi-agent Reinforcement Learning with Binary Action Agents—0
EasyRL: A Simple and Extensible Reinforcement Learning Framework—0
Integrating Deep Reinforcement Learning Networks with Health System SimulationsCode1
Implicit Distributional Reinforcement LearningCode1
OtoWorld: Towards Learning to Separate by Learning to MoveCode1
EVO-RL: Evolutionary-Driven Reinforcement Learning—0
Concept and the implementation of a tool to convert industry 4.0 environments modeled as FSM to an OpenAI Gym wrapper—0
Experience Replay with Likelihood-free Importance WeightsCode1
Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance Guarantees—0
WD3: Taming the Estimation Bias in Deep Reinforcement Learning—0
Data Driven Control with Learned Dynamics: Model-Based versus Model-Free Approach—0
Balancing a CartPole System with Reinforcement Learning -- A Tutorial—0
Refined Continuous Control of DDPG Actors via Parametrised Activation—0
An FPGA-Based On-Device Reinforcement Learning Approach using Online Sequential Learning—0
Reinforcement Learning with Augmented DataCode1
Analyzing Reinforcement Learning Benchmarks with Random Weight GuessingCode0
Policy Gradient using Weak Derivatives for Reinforcement Learning—0
Model-based actor-critic: GAN (model generator) + DRL (actor-critic) => AGI—0
Neural Game Engine: Accurate learning of generalizable forward models from pixelsCode1
Human AI interaction loop training: New approach for interactive reinforcement learning—0
Contextual Policy Transfer in Reinforcement Learning Domains via Deep Mixtures-of-Experts—0
State-only Imitation with Transition Dynamics MismatchCode1
Behavior Cloning in OpenAI using Case Based Reasoning—0
Adaptive Temporal Difference Learning with Linear Function Approximation—0
Adaptive Experience Selection for Policy Gradient—0
PDDLGym: Gym Environments from PDDL ProblemsCode1
Discrete Action On-Policy Learning with Action-Value CriticCode0
Continuous-action Reinforcement Learning for Playing Racing Games: Comparing SPG to PPOCode0
Sample-based Distributional Policy Gradient—0
Blue River Controls: A toolkit for Reinforcement Learning Control Systems on HardwareCode1
Adaptive Droplet Routing in Digital Microfluidic Biochips Using Deep Reinforcement Learning—0
Way Off-Policy Batch Deep Reinforcement Learning of Human Preferences in Dialog—0
SLM Lab: A Comprehensive Benchmark and Modular Software Framework for Reproducible Deep Reinforcement LearningCode0
Taming an autonomous surface vehicle for path following and collision avoidance using deep reinforcement learning—0
Sepsis World Model: A MIMIC-based OpenAI Gym "World Model" Simulator for Sepsis Treatment—0
The PlayStation Reinforcement Learning Environment (PSXLE)Code0
Playing Games in the Dark: An approach for cross-modality transfer in reinforcement learningCode0
Accelerating Reinforcement Learning with Suboptimal Guidance—0
Gym-Ignition: Reproducible Robotic Simulations for Reinforcement LearningCode0
Challenging On Car Racing Problem from OpenAI gym—0
Towards a Reinforcement Learning Environment Toolbox for Intelligent Electric Motor ControlCode0
Zap Q-Learning With Nonlinear Function Approximation—0
MVFST-RL: An Asynchronous RL Framework for Congestion Control with Delayed ActionsCode0
TorchBeast: A PyTorch Platform for Distributed RLCode0
Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement LearningCode1
SURREAL-System: Fully-Integrated Stack for Distributed Deep Reinforcement Learning—0
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous ControlCode0
Advantage Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning—0
Self-Supervised State-Control through Intrinsic Mutual Information RewardsCode0
MoET: Interpretable and Verifiable Reinforcement Learning via Mixture of Expert Trees—0
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All datasetsAnt-v4HalfCheetah-v4Hopper-v4Humanoid-v4Walker2d-v4Ant-v2CartPole-v1HalfCheetah-v2Hopper-v2LunarLander-v2Mountain CarPendulum-v1

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MEowAverage Return6,586.33—Unverified
2TD3Average Return5,942.55—Unverified
3SACAverage Return5,208.09—Unverified
4DDPGAverage Return1,712.12—Unverified
5PPOAverage Return608.97—Unverified
#ModelMetricClaimedVerifiedStatus
1SACAverage Return15,836.04—Unverified
2DDPGAverage Return14,934.86—Unverified
3TD3Average Return12,026.73—Unverified
4MEowAverage Return10,981.47—Unverified
5PPOAverage Return6,006.11—Unverified
#ModelMetricClaimedVerifiedStatus
1MEowAverage Return3,332.99—Unverified
2TD3Average Return3,319.98—Unverified
3SACAverage Return2,882.56—Unverified
4DDPGAverage Return1,290.24—Unverified
5PPOAverage Return790.77—Unverified
#ModelMetricClaimedVerifiedStatus
1MEowAverage Return6,923.22—Unverified
2SACAverage Return6,211.5—Unverified
3PPOAverage Return925.89—Unverified
4TD3Average Return198.44—Unverified
5DDPGAverage Return139.14—Unverified
#ModelMetricClaimedVerifiedStatus
1SACAverage Return5,745.27—Unverified
2MEowAverage Return5,526.66—Unverified
3DDPGAverage Return2,994.54—Unverified
4PPOAverage Return2,739.81—Unverified
5TD3Average Return2,612.74—Unverified
#ModelMetricClaimedVerifiedStatus
1TLAMean Reward5,163.54—Unverified
2AWRMean Reward5,067—Unverified
#ModelMetricClaimedVerifiedStatus
1Orthogonal decision treeAverage Return500—Unverified
2Oblique decision treeAverage Return500—Unverified
#ModelMetricClaimedVerifiedStatus
1TLAMean Reward9,571.99—Unverified
2AWRMean Reward9,136—Unverified
#ModelMetricClaimedVerifiedStatus
1TLAMean Reward3,458.22—Unverified
2AWRMean Reward3,405—Unverified
#ModelMetricClaimedVerifiedStatus
1Oblique decision treeAverage Return272.14—Unverified
2AWRAverage Return229—Unverified
#ModelMetricClaimedVerifiedStatus
1Orthogonal decision treeAverage Return-101.72—Unverified
2Oblique decision treeAverage Return-106.02—Unverified
#ModelMetricClaimedVerifiedStatus
1TLA with Hierarchical Reward FunctionsMean Reward-125.02—Unverified
2TLAMean Reward-154.92—Unverified
#ModelMetricClaimedVerifiedStatus
1AWRMean Reward5,813—Unverified
2TLAMean Reward3,878.41—Unverified
#ModelMetricClaimedVerifiedStatus
1AWRAverage Return4,996—Unverified
#ModelMetricClaimedVerifiedStatus
1TLAMean Reward9,356.67—Unverified
#ModelMetricClaimedVerifiedStatus
1TLAMean Reward1,000—Unverified
#ModelMetricClaimedVerifiedStatus
1TLAMean Reward93.88—Unverified