OpenAI Gym

Description from the archive archive 2025-07-28; Papers-with-Code links inside it are rewritten to this site.

Benchmarks archive 2025-07-28

17 leaderboard tables shown for this task, 17 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 17 until expanded.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 179 papers with code (382 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Proximal Policy Optimization Algorithms
  20 Jul 2017 188 repositories listed Syntology ran 99 of 176 samples · 77 unverified · 94 pointer-only (licence)
  We propose a new family of policy gradient methods for reinforcement learning, which alternate between sampling data through interaction with the environment, and optimizing a "surrogate" objective function using…
• Continuous control with deep reinforcement learning
  9 Sep 2015 161 repositories listed Syntology ran 158 of 306 samples · 148 unverified · 163 pointer-only (licence)
  We adapt the ideas underlying the success of Deep Q-Learning to the continuous action domain.
• Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
  4 Jan 2018 86 repositories listed Syntology ran 91 of 148 samples · 57 unverified · 66 pointer-only (licence)
  A platform for Applied Reinforcement Learning (Applied RL)
• Addressing Function Approximation Error in Actor-Critic Methods
  26 Feb 2018 67 repositories listed Syntology ran 9 of 36 samples · 27 unverified · 20 pointer-only (licence)
  In value-based reinforcement learning methods such as deep Q-learning, function approximation errors are known to lead to overestimated value estimates and suboptimal policies.
• Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research
  26 Feb 2018 28 repositories listed
  The purpose of this technical report is two-fold.
• Decision Transformer: Reinforcement Learning via Sequence Modeling
  2 Jun 2021 20 repositories listed Syntology ran 17 of 26 samples · 9 unverified · 6 pointer-only (licence)
  In particular, we present Decision Transformer, an architecture that casts the problem of RL as conditional sequence modeling.
• Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
  1 Oct 2019 6 repositories listed
  In this paper, we aim to develop a simple and scalable reinforcement learning algorithm that uses standard supervised learning methods as subroutines.
• Deep Recurrent Q-Learning for Partially Observable MDPs
  23 Jul 2015 5 repositories listed Syntology ran 0 of 2 samples · 2 unverified
  Deep Reinforcement Learning has yielded proficient controllers for complex tasks.
• Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy Imitation
  23 Jun 2023 4 repositories listed
  Despite its simplicity this baseline is competitive with meta-learning methods on a variety of conditions and is able to imitate target policies trained on unseen variations of the original environment.
• Deep Reinforcement Learning for Playing 2.5D Fighting Games
  5 May 2018 4 repositories listed
  Deep reinforcement learning has shown its success in game playing.
• Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control
  3 Mar 2021 3 repositories listed
  Robotic simulators are crucial for academic research and education as well as the development of safety-critical applications.
• Implicit Distributional Reinforcement Learning
  13 Jul 2020 3 repositories listed Syntology ran 4 of 6 samples · 2 unverified
  To improve the sample efficiency of policy-gradient based reinforcement learning algorithms, we propose implicit distributional actor-critic (IDAC) that consists of a distributional critic, built on two deep generator…
• TorchBeast: A PyTorch Platform for Distributed RL
  8 Oct 2019 3 repositories listed Syntology ran 4 of 9 samples · 5 unverified · 3 pointer-only (licence)
  TorchBeast is a platform for reinforcement learning (RL) research in PyTorch.
• Maximum Entropy-Regularized Multi-Goal Reinforcement Learning
  21 May 2019 3 repositories listed
  This objective encourages the agent to maximize the expected return, as well as to achieve more diverse goals.
• Decision Mamba Architectures
  13 May 2024 2 repositories listed
  In this work, we introduce two novel methods, Decision Mamba (DM) and Hierarchical Decision Mamba (HDM), aimed at enhancing the performance of the Transformer models.
• For SALE: State-Action Representation Learning for Deep Reinforcement Learning
  4 Jun 2023 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 1 pointer-only (licence)
  In the field of reinforcement learning (RL), representation learning is a proven tool for complex image-based tasks, but is often overlooked for environments with low-level states, such as physical control problems.
• MO-Gym: A Library of Multi-Objective Reinforcement Learning Environments
  30 Nov 2022 2 repositories listed
  We introduce MO-Gym, an extensible library containing a diverse set of multi-objective reinforcement learning environments.
• pyRDDLGym: From RDDL to Gym Environments
  11 Nov 2022 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  We present pyRDDLGym, a Python framework for auto-generation of OpenAI Gym environments from RDDL declerative description.
• COOL-MC: A Comprehensive Tool for Reinforcement Learning and Model Checking
  15 Sep 2022 2 repositories listed
  This paper presents COOL-MC, a tool that integrates state-of-the-art reinforcement learning (RL) and model checking.
• Bayesian Soft Actor-Critic: A Directed Acyclic Strategy Graph Based Deep Reinforcement Learning
  11 Aug 2022 2 repositories listed
  Adopting reasonable strategies is challenging but crucial for an intelligent agent with limited resources working in hazardous, unstructured, and dynamic environments to improve the system's utility, decrease the…
• Quantum Deep Reinforcement Learning for Robot Navigation Tasks
  24 Feb 2022 2 repositories listed Syntology ran 0 of 9 samples · 9 unverified
  We utilize hybrid quantum deep reinforcement learning to learn navigation tasks for a simple, wheeled robot in simulated environments of increasing complexity.
• MarsExplorer: Exploration of Unknown Terrains via Deep Reinforcement Learning and Procedurally Generated Environments
  21 Jul 2021 2 repositories listed
  This paper is an initial endeavor to bridge the gap between powerful Deep Reinforcement Learning methodologies and the problem of exploration/coverage of unknown terrains.
• An Open-Source Multi-Goal Reinforcement Learning Environment for Robotic Manipulation with Pybullet
  12 May 2021 2 repositories listed
  This work re-implements the OpenAI Gym multi-goal robotic manipulation environment, originally based on the commercial Mujoco engine, onto the open-source Pybullet engine.
• CropGym: a Reinforcement Learning Environment for Crop Management
  9 Apr 2021 2 repositories listed
  Nitrogen fertilizers have a detrimental effect on the environment, which can be reduced by optimizing fertilizer management strategies.
• Improving Model-Based Reinforcement Learning with Internal State Representations through Self-Supervision
  10 Feb 2021 2 repositories listed
  Using a model of the environment, reinforcement learning agents can plan their future moves and achieve superhuman performance in board games like Chess, Shogi, and Go, while remaining relatively sample-efficient.
• Neurogenetic Programming Framework for Explainable Reinforcement Learning
  8 Feb 2021 2 repositories listed
  Automatic programming, the task of generating computer programs compliant with a specification without a human developer, is usually tackled either via genetic programming methods based on mutation and recombination of…
• Reinforcement Learning for Control of Valves
  29 Dec 2020 2 repositories listed
  This paper is a study of reinforcement learning (RL) as an optimal-control strategy for control of nonlinear valves.
• SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation
  14 Nov 2020 2 repositories listed
  Further, we evaluate a variety of algorithms on these tasks and highlight challenges for reinforcement learning algorithms, including dealing with a state representation that has a high intrinsic dimensionality and is…
• Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers
  11 Nov 2020 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  We present Ecole, a new library to simplify machine learning research for combinatorial optimization.
• EpidemiOptim: A Toolbox for the Optimization of Control Policies in Epidemiological Models
  9 Oct 2020 2 repositories listed
  Epidemiologists model the dynamics of epidemics in order to propose control strategies based on pharmaceutical and non-pharmaceutical interventions (contact limitation, lock down, vaccination, etc).

Syntology lines on 12 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.