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

Showing 101–150 of 382 papers

TitleStatusHype
pyRDDLGym: From RDDL to Gym EnvironmentsCode1
Design Process is a Reinforcement Learning ProblemCode1
DIAMBRA Arena: a New Reinforcement Learning Platform for Research and ExperimentationCode2
Sufficient Exploration for Convex Q-learning—0
Long N-step Surrogate Stage Reward to Reduce Variances of Deep Reinforcement Learning in Complex Problems—0
Reinforcement Learning Approach for Multi-Agent Flexible Scheduling Problems—0
Elastic Step DQN: A novel multi-step algorithm to alleviate overestimation in Deep QNetworks—0
CaiRL: A High-Performance Reinforcement Learning Environment ToolkitCode1
COOL-MC: A Comprehensive Tool for Reinforcement Learning and Model CheckingCode1
Distilling Deep RL Models Into Interpretable Neuro-Fuzzy Systems—0
A Deep Reinforcement Learning Strategy for UAV Autonomous Landing on a Platform—0
Project proposal: A modular reinforcement learning based automated theorem proverCode0
Cluster-based Sampling in Hindsight Experience Replay for Robotic Tasks (Student Abstract)—0
MARTI-4: new model of human brain, considering neocortex and basal ganglia -- learns to play Atari game by reinforcement learning on a single CPU—0
Quality Diversity Evolutionary Learning of Decision Trees—0
Bayesian Soft Actor-Critic: A Directed Acyclic Strategy Graph Based Deep Reinforcement LearningCode1
Implicit Two-Tower Policies—0
RangL: A Reinforcement Learning Competition Platform—0
Safe and Robust Experience Sharing for Deterministic Policy Gradient AlgorithmsCode0
Modelling non-reinforced preferences using selective attention—0
Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policies—0
Adversarial joint attacks on legged robots—0
Adversarial Body Shape Search for Legged Robots—0
Unified Distributed EnvironmentCode0
JORLDY: a fully customizable open source framework for reinforcement learningCode2
MR-iNet Gym: Framework for Edge Deployment of Deep Reinforcement Learning on Embedded Software Defined Radio—0
Remember and Forget Experience Replay for Multi-Agent Reinforcement Learning—0
Multitask Neuroevolution for Reinforcement Learning with Long and Short Episodes—0
Gym-saturation: an OpenAI Gym environment for saturation provers—0
Andes_gym: A Versatile Environment for Deep Reinforcement Learning in Power SystemsCode0
Avalanche RL: a Continual Reinforcement Learning LibraryCode1
Provably Efficient Convergence of Primal-Dual Actor-Critic with Nonlinear Function Approximation—0
Quantum Deep Reinforcement Learning for Robot Navigation TasksCode0
QuadSim: A Quadcopter Rotational Dynamics Simulation Framework For Reinforcement Learning AlgorithmsCode1
skrl: Modular and Flexible Library for Reinforcement Learning—0
Soft Actor-Critic with Inhibitory Networks for Faster Retraining—0
Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization—0
Deep Q-learning: a robust control approachCode0
Direct Mutation and Crossover in Genetic Algorithms Applied to Reinforcement Learning Tasks—0
A Surrogate-Assisted Controller for Expensive Evolutionary Reinforcement Learning—0
Multi-Agent Reinforcement Learning via Adaptive Kalman Temporal Difference and Successor Representation—0
Teaching a Robot to Walk Using Reinforcement Learning—0
Control-Tutored Reinforcement Learning: Towards the Integration of Data-Driven and Model-Based Control—0
Continuous Control With Ensemble Deep Deterministic Policy GradientsCode0
TMM-Fast: A Transfer Matrix Computation Package for Multilayer Thin-Film OptimizationCode1
Adaptively Calibrated Critic Estimates for Deep Reinforcement LearningCode0
VisualEnv: visual Gym environments with Blender—0
AWD3: Dynamic Reduction of the Estimation Bias—0
DriverGym: Democratising Reinforcement Learning for Autonomous Driving—0
Proximal Policy Optimization with Continuous Bounded Action Space via the Beta Distribution—0
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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