Model-based Reinforcement Learning

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Datasets archive 2025-07-28

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Most implemented papers archive 2025-07-28

30 shown of 234 papers with code (708 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.

• When to Trust Your Model: Model-Based Policy Optimization
  19 Jun 2019 11 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Designing effective model-based reinforcement learning algorithms is difficult because the ease of data generation must be weighed against the bias of model-generated data.
• 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.
• 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.
• TD-MPC2: Scalable, Robust World Models for Continuous Control
  25 Oct 2023 3 repositories listed Syntology ran 12 of 16 samples · 4 unverified
  TD-MPC is a model-based reinforcement learning (RL) algorithm that performs local trajectory optimization in the latent space of a learned implicit (decoder-free) world model.
• TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction
  7 Mar 2023 3 repositories listed
  We present TrafficBots, a multi-agent policy built upon motion prediction and end-to-end driving, and based on TrafficBots we obtain a world model tailored for the planning module of autonomous vehicles.
• Planning with Diffusion for Flexible Behavior Synthesis
  20 May 2022 3 repositories listed
  Model-based reinforcement learning methods often use learning only for the purpose of estimating an approximate dynamics model, offloading the rest of the decision-making work to classical trajectory optimizers.
• Temporal Predictive Coding For Model-Based Planning In Latent Space
  14 Jun 2021 3 repositories listed Syntology ran 2 of 9 samples · 7 unverified
  High-dimensional observations are a major challenge in the application of model-based reinforcement learning (MBRL) to real-world environments.
• Integrated Decision and Control: Towards Interpretable and Computationally Efficient Driving Intelligence
  18 Mar 2021 3 repositories listed
  In this paper, we present an interpretable and computationally efficient framework called integrated decision and control (IDC) for automated vehicles, which decomposes the driving task into static path planning and…
• Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation
  10 Nov 2019 3 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  Reinforcement learning is well suited for optimizing policies of recommender systems.
• Dynamics-Aware Unsupervised Discovery of Skills
  2 Jul 2019 3 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  Conventionally, model-based reinforcement learning (MBRL) aims to learn a global model for the dynamics of the environment.
• Machine Learning and System Identification for Estimation in Physical Systems
  5 Jun 2019 3 repositories listed
  The main approach to estimation and learning adopted is optimization based.
• PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos
  4 Feb 2019 3 repositories listed
  Previously, the exploding gradient problem has been explained to be central in deep learning and model-based reinforcement learning, because it causes numerical issues and instability in optimization.
• Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning
  6 Mar 2018 3 repositories listed
  Finally, we assess the performance of the algorithm for learning motor controllers for a six legged autonomous underwater vehicle.
• Model-based Reinforcement Learning for Parameterized Action Spaces
  3 Apr 2024 2 repositories listed Syntology ran 9 of 9 samples · 0 unverified · 9 pointer-only (licence)
  We propose a novel model-based reinforcement learning algorithm -- Dynamics Learning and predictive control with Parameterized Actions (DLPA) -- for Parameterized Action Markov Decision Processes (PAMDPs).
• The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning
  19 Feb 2024 2 repositories listed
  We show that this truncation of rollouts results in a set of edge-of-reach states at which we are effectively ``bootstrapping from the void.''
• Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models
  6 Oct 2023 2 repositories listed Syntology ran 7 of 9 samples · 2 unverified
  By leveraging the in-context learning ability of LMs, we integrate Monte Carlo Tree Search into LATS to enable LMs as agents, along with LM-powered value functions and self-reflections for proficient exploration and…
• Predictive Experience Replay for Continual Visual Control and Forecasting
  12 Mar 2023 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  In this paper, we present a new continual learning approach for visual dynamics modeling and explore its efficacy in visual control and forecasting.
• Predictable MDP Abstraction for Unsupervised Model-Based RL
  8 Feb 2023 2 repositories listed
  A key component of model-based reinforcement learning (RL) is a dynamics model that predicts the outcomes of actions.
• The Effectiveness of World Models for Continual Reinforcement Learning
  29 Nov 2022 2 repositories listed
  World models power some of the most efficient reinforcement learning algorithms.
• An Experimental Design Perspective on Model-Based Reinforcement Learning
  9 Dec 2021 2 repositories listed Syntology ran 4 of 4 samples · 0 unverified
  In particular, we leverage ideas from Bayesian optimal experimental design to guide the selection of state-action queries for efficient learning.
• Gradient Information Matters in Policy Optimization by Back-propagating through Model
  29 Sep 2021 2 repositories listed
  Then we proposed a two-model-based learning method to control the prediction error and the gradient error.
• Planning in Stochastic Environments with a Learned Model
  29 Sep 2021 2 repositories listed
  However, previous instantiations of this approach were limited to the use of deterministic models.
• MBRL-Lib: A Modular Library for Model-based Reinforcement Learning
  20 Apr 2021 2 repositories listed
  MBRL-Lib is designed as a platform for both researchers, to easily develop, debug and compare new algorithms, and non-expert user, to lower the entry-bar of deploying state-of-the-art algorithms.
• Online and Offline Reinforcement Learning by Planning with a Learned Model
  13 Apr 2021 2 repositories listed
  Combining Reanalyse with the MuZero algorithm, we introduce MuZero Unplugged, a single unified algorithm for any data budget, including offline RL.
• Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow
  26 Mar 2021 2 repositories listed
  This paves the way for new research directions, e.
• 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.
• Understanding and Mitigating the Limitations of Prioritized Experience Replay
  19 Jul 2020 2 repositories listed
  Prioritized Experience Replay (ER) has been empirically shown to improve sample efficiency across many domains and attracted great attention; however, there is little theoretical understanding of why such prioritized…
• The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning
  7 Jul 2020 2 repositories listed Syntology ran 1 of 2 samples · 1 unverified
  For example, the common single-task sample-efficiency metric conflates improvements due to model-based learning with various other aspects, such as representation learning, making it difficult to assess true progress on…
• Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning
  14 May 2020 2 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 2 pointer-only (licence)
  Model-based reinforcement learning (RL) enjoys several benefits, such as data-efficiency and planning, by learning a model of the environment's dynamics.
• Objective Mismatch in Model-based Reinforcement Learning
  11 Feb 2020 2 repositories listed
  In our experiments, we study this objective mismatch issue and demonstrate that the likelihood of one-step ahead predictions is not always correlated with control performance.

Syntology lines on 13 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.