OpenAI Gym

OpenAI Gym is a toolkit that provides a variety of environments for developing and evaluating reinforcement learning algorithms, particularly in continuous control tasks.

Papers using OpenAI Gym (38)

Reflex: Reinforcement Learning with Reflection Symmetry Exploitation in State-Based Continuous Control2026Evolutionary Discovery of Reinforcement Learning Algorithms via Large Language Models2026Reinforcement Learning for Parameterized Quantum State Preparation: A Comparative Study2026Reward Learning through Ranking Mean Squared Error2026Enhancing Control Policy Smoothness by Aligning Actions with Predictions from Preceding States2026Know your Trajectory -- Trustworthy Reinforcement Learning deployment through Importance-Based Trajectory Analysis2025STACHE: Local Black-Box Explanations for Reinforcement Learning Policies2025LacaDM: A Latent Causal Diffusion Model for Multiobjective Reinforcement Learning2025Mind Your Entropy: From Maximum Entropy to Trajectory Entropy-Constrained RL2025Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance2025Prompted Policy Search: Reinforcement Learning through Linguistic and Numerical Reasoning in LLMs2025A Forensic Analysis of Synthetic Data in RL: Diagnosing and Solving Algorithmic Failures in Model-Based Policy Optimization2025ES-C51: Expected Sarsa Based C51 Distributional Reinforcement Learning Algorithm2025Off-policy Reinforcement Learning with Model-based Exploration Augmentation2025Prompt Informed Reinforcement Learning for Visual Coverage Path Planning2025IN-RIL: Interleaved Reinforcement and Imitation Learning for Policy Fine-Tuning2025Improving the Data-efficiency of Reinforcement Learning by Warm-starting with LLM2025Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions2025ReaCritic: Reasoning Transformer-based DRL Critic-model Scaling For Wireless Networks2025VIRAL: Vision-grounded Integration for Reward design And Learning2025Learning from Less: SINDy Surrogates in RL2025Stone Soup Multi-Target Tracking Feature Extraction For Autonomous Search And Track In Deep Reinforcement Learning Environment2025Robustness Evaluation of Offline Reinforcement Learning for Robot Control Against Action Perturbations2024Inversely Learning Transferable Rewards via Abstracted States2025Session-Level Dynamic Ad Load Optimization using Offline Robust Reinforcement Learning2025Double Successive Over-Relaxation Q-Learning with an Extension to Deep Reinforcement Learning2024To Switch or Not to Switch? Balanced Policy Switching in Offline Reinforcement Learning2024SwiftRL: Towards Efficient Reinforcement Learning on Real Processing-In-Memory Systems2024 · 9 citesMOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement Learning2024 · 5 citesDEER: A Delay-Resilient Framework for Reinforcement Learning with Variable Delays2024 · 2 citesBenchmarking Smoothness and Reducing High-Frequency Oscillations in Continuous Control Policies2024 · 2 citesNoisy Spiking Actor Network for Exploration2024 · 1 citesStealing That Free Lunch: Exposing the Limits of Dyna-Style Reinforcement Learning2024 · 1 citesOff-OAB: Off-Policy Policy Gradient Method with Optimal Action-Dependent Baseline2024OMPO: A Unified Framework for RL under Policy and Dynamics Shifts2024Mamba as Decision Maker: Exploring Multi-scale Sequence Modeling in Offline Reinforcement Learning2024Adaptive Planning with Generative Models under Uncertainty2024MAGICS: Adversarial RL with Minimax Actors Guided by Implicit Critic Stackelberg for Convergent Neural Synthesis of Robot Safety2024