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 51–100 of 382 papers

TitleStatusHype
Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning AlgorithmsCode1
Resilient Control of Networked Microgrids using Vertical Federated Reinforcement Learning: Designs and Real-Time Test-Bed Validations—0
Guaranteeing Control Requirements via Reward Shaping in Reinforcement LearningCode0
Bridging Dimensions: Confident Reachability for High-Dimensional ControllersCode0
Repairing Learning-Enabled Controllers While Preserving What WorksCode0
SDGym: Low-Code Reinforcement Learning Environments using System Dynamics Models—0
Offline Retraining for Online RL: Decoupled Policy Learning to Mitigate Exploration BiasCode1
Neural architecture impact on identifying temporally extended Reinforcement Learning tasks—0
Optimizing with Low Budgets: a Comparison on the Black-box Optimization Benchmarking Suite and OpenAI Gym—0
Implicit Sensing in Traffic Optimization: Advanced Deep Reinforcement Learning Techniques—0
gym-saturation: Gymnasium environments for saturation provers (System description)—0
Attention Loss Adjusted Prioritized Experience Replay—0
Statistically Efficient Variance Reduction with Double Policy Estimation for Off-Policy Evaluation in Sequence-Modeled Reinforcement Learning—0
Distributionally Robust Statistical Verification with Imprecise Neural Networks—0
qgym: A Gym for Training and Benchmarking RL-Based Quantum CompilationCode1
On Combining Expert Demonstrations in Imitation Learning via Optimal Transport—0
Scaling Distributed Multi-task Reinforcement Learning with Experience Sharing—0
Dynamic Observation Policies in Observation Cost-Sensitive Reinforcement LearningCode0
Learning Environment Models with Continuous Stochastic Dynamics—0
Correcting discount-factor mismatch in on-policy policy gradient methods—0
Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy ImitationCode0
Deep Reinforcement Learning for ESG financial portfolio management—0
Mimicking Better by Matching the Approximate Action DistributionCode0
Active Inference in Hebbian Learning Networks—0
Risk-Aware Reward Shaping of Reinforcement Learning Agents for Autonomous DrivingCode0
For SALE: State-Action Representation Learning for Deep Reinforcement LearningCode1
Optimizing Attention and Cognitive Control Costs Using Temporally-Layered ArchitecturesCode0
Discovering Individual Rewards in Collective Behavior through Inverse Multi-Agent Reinforcement Learning—0
Rethinking Population-assisted Off-policy Reinforcement Learning—0
Gym-preCICE: Reinforcement Learning Environments for Active Flow Control—0
Signal Novelty Detection as an Intrinsic Reward for RoboticsCode0
Exact and Cost-Effective Automated Transformation of Neural Network Controllers to Decision Tree Controllers—0
Causal Repair of Learning-enabled Cyber-physical Systems—0
Generative Adversarial Neuroevolution for Control Behaviour ImitationCode0
Neuroevolution of Recurrent Architectures on Control TasksCode0
Soft-Bellman Equilibrium in Affine Markov Games: Forward Solutions and Inverse LearningCode0
Graph Decision Transformer—0
A Strategy-Oriented Bayesian Soft Actor-Critic Model—0
Local Environment Poisoning Attacks on Federated Reinforcement Learning—0
Double A3C: Deep Reinforcement Learning on OpenAI Gym Games—0
ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints—0
EvoX: A Distributed GPU-accelerated Framework for Scalable Evolutionary ComputationCode4
Neural Episodic Control with State Abstraction—0
PushWorld: A benchmark for manipulation planning with tools and movable obstaclesCode1
Asynchronous Deep Double Duelling Q-Learning for Trading-Signal Execution in Limit Order Book Markets—0
Off-Policy Reinforcement Learning with Loss Function Weighted by Temporal Difference Error—0
Enhancing Cyber Resilience of Networked Microgrids using Vertical Federated Reinforcement Learning—0
Robust Policy Optimization in Deep Reinforcement LearningCode0
CT-DQN: Control-Tutored Deep Reinforcement Learning—0
MO-Gym: A Library of Multi-Objective Reinforcement Learning EnvironmentsCode2
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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