Deep Reinforcement Learning

Benchmarks archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 1,739 papers with code (5,822 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.

• 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.
• Playing Atari with Deep Reinforcement Learning
  19 Dec 2013 112 repositories listed Syntology ran 56 of 117 samples · 61 unverified · 56 pointer-only (licence)
  We present the first deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning.
• Deep Reinforcement Learning with Double Q-learning
  22 Sep 2015 97 repositories listed Syntology ran 55 of 106 samples · 51 unverified · 57 pointer-only (licence)
  The popular Q-learning algorithm is known to overestimate action values under certain conditions.
• 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)
• Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
  7 Jun 2017 86 repositories listed Syntology ran 75 of 143 samples · 68 unverified · 99 pointer-only (licence)
  We explore deep reinforcement learning methods for multi-agent domains.
• Dueling Network Architectures for Deep Reinforcement Learning
  20 Nov 2015 73 repositories listed Syntology ran 5 of 11 samples · 6 unverified · 6 pointer-only (licence)
  In recent years there have been many successes of using deep representations in reinforcement learning.
• Asynchronous Methods for Deep Reinforcement Learning
  4 Feb 2016 70 repositories listed Syntology ran 38 of 95 samples · 57 unverified · 12 pointer-only (licence)
  We propose a conceptually simple and lightweight framework for deep reinforcement learning that uses asynchronous gradient descent for optimization of deep neural network controllers.
• Rainbow: Combining Improvements in Deep Reinforcement Learning
  6 Oct 2017 34 repositories listed Syntology ran 2 of 6 samples · 4 unverified · 1 pointer-only (licence)
  The deep reinforcement learning community has made several independent improvements to the DQN algorithm.
• A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem
  30 Jun 2017 30 repositories listed
  They are, along with a number of recently reviewed or published portfolio-selection strategies, examined in three back-test experiments with a trading period of 30 minutes in a cryptocurrency market.
• Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
  6 Jun 2015 29 repositories listed Syntology ran 4 of 4 samples · 0 unverified · 4 pointer-only (licence)
  In comparison, Bayesian models offer a mathematically grounded framework to reason about model uncertainty, but usually come with a prohibitive computational cost.
• Exploration by Random Network Distillation
  30 Oct 2018 22 repositories listed Syntology ran 26 of 43 samples · 17 unverified · 15 pointer-only (licence)
  In particular we establish state of the art performance on Montezuma's Revenge, a game famously difficult for deep reinforcement learning methods.
• RL²: Fast Reinforcement Learning via Slow Reinforcement Learning
  9 Nov 2016 19 repositories listed Syntology ran 11 of 21 samples · 10 unverified
  The activations of the RNN store the state of the "fast" RL algorithm on the current (previously unseen) MDP.
• Gradient Surgery for Multi-Task Learning
  19 Jan 2020 18 repositories listed Syntology ran 7 of 10 samples · 3 unverified · 4 pointer-only (licence)
  While deep learning and deep reinforcement learning (RL) systems have demonstrated impressive results in domains such as image classification, game playing, and robotic control, data efficiency remains a major challenge.
• Flow: A Modular Learning Framework for Mixed Autonomy Traffic
  16 Oct 2017 16 repositories listed Syntology ran 1 of 17 samples · 16 unverified
  Furthermore, in single-lane traffic, a small neural network control law with only local observation is found to eliminate stop-and-go traffic - surpassing all known model-based controllers to achieve near-optimal…
• Distributed Prioritized Experience Replay
  2 Mar 2018 15 repositories listed Syntology ran 0 of 15 samples · 15 unverified
  We propose a distributed architecture for deep reinforcement learning at scale, that enables agents to learn effectively from orders of magnitude more data than previously possible.
• Noisy Networks for Exploration
  30 Jun 2017 15 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)
  We introduce NoisyNet, a deep reinforcement learning agent with parametric noise added to its weights, and show that the induced stochasticity of the agent's policy can be used to aid efficient exploration.
• Benchmarking Deep Reinforcement Learning for Continuous Control
  22 Apr 2016 15 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  Recently, researchers have made significant progress combining the advances in deep learning for learning feature representations with reinforcement learning.
• Dopamine: A Research Framework for Deep Reinforcement Learning
  14 Dec 2018 13 repositories listed Syntology ran 0 of 16 samples · 16 unverified
  Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
• Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning
  18 Dec 2017 12 repositories listed Syntology ran 4 of 5 samples · 1 unverified · 4 pointer-only (licence)
  Here we demonstrate they can: we evolve the weights of a DNN with a simple, gradient-free, population-based genetic algorithm (GA) and it performs well on hard deep RL problems, including Atari and humanoid locomotion.
• Off-Policy Deep Reinforcement Learning without Exploration
  7 Dec 2018 10 repositories listed Syntology ran 13 of 14 samples · 1 unverified · 9 pointer-only (licence)
  Many practical applications of reinforcement learning constrain agents to learn from a fixed batch of data which has already been gathered, without offering further possibility for data collection.
• StarCraft II: A New Challenge for Reinforcement Learning
  16 Aug 2017 10 repositories listed Syntology ran 5 of 5 samples · 0 unverified · 2 pointer-only (licence)
  Finally, we present initial baseline results for canonical deep reinforcement learning agents applied to the StarCraft II domain.
• Parameter Space Noise for Exploration
  6 Jun 2017 10 repositories listed Syntology ran 4 of 5 samples · 1 unverified · 5 pointer-only (licence)
  Combining parameter noise with traditional RL methods allows to combine the best of both worlds.
• Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks
  14 Jun 2020 9 repositories listed Syntology ran 7 of 12 samples · 5 unverified · 7 pointer-only (licence)
  Multi-agent deep reinforcement learning (MARL) suffers from a lack of commonly-used evaluation tasks and criteria, making comparisons between approaches difficult.
• rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch
  3 Sep 2019 9 repositories listed Syntology ran 0 of 10 samples · 10 unverified
  rlpyt is designed as a high-throughput code base for small- to medium-scale research in deep RL.
• Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model
  1 Jul 2019 9 repositories listed Syntology ran 3 of 11 samples · 8 unverified
  Deep reinforcement learning (RL) algorithms can use high-capacity deep networks to learn directly from image observations.
• Practical Deep Reinforcement Learning Approach for Stock Trading
  19 Nov 2018 9 repositories listed
  We explore the potential of deep reinforcement learning to optimize stock trading strategy and thus maximize investment return.
• Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models
  30 May 2018 9 repositories listed Syntology ran 12 of 19 samples · 7 unverified · 17 pointer-only (licence)
  Model-based reinforcement learning (RL) algorithms can attain excellent sample efficiency, but often lag behind the best model-free algorithms in terms of asymptotic performance.
• Solving the Rubik's Cube Without Human Knowledge
  18 May 2018 9 repositories listed Syntology ran 4 of 4 samples · 0 unverified · 4 pointer-only (licence)
  A generally intelligent agent must be able to teach itself how to solve problems in complex domains with minimal human supervision.
• Population Based Training of Neural Networks
  27 Nov 2017 9 repositories listed
  Neural networks dominate the modern machine learning landscape, but their training and success still suffer from sensitivity to empirical choices of hyperparameters such as model architecture, loss function, and…
• Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning
  8 Aug 2017 9 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  Model-free deep reinforcement learning algorithms have been shown to be capable of learning a wide range of robotic skills, but typically require a very large number of samples to achieve good performance.

Syntology lines on 27 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.