世界模型

MInCo: Mitigating Information Conflicts in Distracted Visual Model-based Reinforcement Learning

Shiguang Sun, Hanbo Zhang, Zeyang Liu, Xinrui Yang, Lipeng Wan, Xingyu Chen, Xuguang Lan

机构 * National Key Laboratory of Human-Machine Hybrid Augmented Intelligence（人机混合增强智能国家重点实验室） ； National Engineering Research Center for Visual Information and Applications（视觉信息与应用国家工程研究中心） ； Institute of Artificial Intelligence and Robotics（人工智能与机器人研究院） ； Xi’an Jiaotong University（西安交通大学） ； National University of Singapore（新加坡国立大学） 纠错

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；latent dynamics(abstract)；分类 cs.LG；dynamics model(abstract)

Enhancing Traffic Signal Control through Model-based Reinforcement Learning and Policy Reuse

Yihong Li, Chengwei Zhang, Furui Zhan, Wanting Liu, Kailing Zhou, Longji Zheng

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；environment model(abstract)；分类 cs.AI、cs.MA

Safe Deep Model-Based Reinforcement Learning with Lyapunov Functions

Harry Zhang

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；model-based RL(abstract)；分类 cs.AI、cs.LG

A Note on Loss Functions and Error Compounding in Model-based Reinforcement Learning

Nan Jiang

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；model-based RL(abstract)；分类 cs.AI、cs.LG

Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function

Ruijie Zheng, Xiyao Wang, Huazhe Xu, Furong Huang

专题命中 模型式强化学习 ：model-based RL(title,abstract)；model-based reinforcement learning(abstract)；分类 cs.LG；dynamics model(abstract)

Comments ICLR 2023

Model-based Reinforcement Learning with Multi-step Plan Value Estimation

Haoxin Lin, Yihao Sun, Jiaji Zhang, Yang Yu

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；model-based RL(abstract)；分类 cs.AI、cs.LG

Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods

Yi Wan, Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Sarath Chandar, Harm van Seijen

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；model-based RL(abstract)；分类 cs.AI、cs.LG

Model-Advantage and Value-Aware Models for Model-Based Reinforcement Learning: Bridging the Gap in Theory and Practice

Nirbhay Modhe, Harish Kamath, Dhruv Batra, Ashwin Kalyan

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；model-based RL(abstract)；分类 cs.AI、cs.LG

Safety Verification of Model Based Reinforcement Learning Controllers

Akshita Gupta, Inseok Hwang

专题命中 模型式强化学习 ：model based reinforcement learning(title)；model-based reinforcement learning(abstract)；model-based RL(abstract)；分类 cs.LG、cs.RO

Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies

Yonathan Efroni, Nadav Merlis, Mohammad Ghavamzadeh, Shie Mannor

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；model-based RL(abstract)；分类 cs.AI、cs.LG

Comments NeurIPS 2019

SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning

Marvin Zhang, Sharad Vikram, Laura Smith, Pieter Abbeel, Matthew J. Johnson, Sergey Levine

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；model-based RL(abstract)；分类 cs.LG、cs.RO

Comments ICML 2019. Project website: https://sites.google.com/view/icml19solar

Intelligent Trainer for Model-Based Reinforcement Learning

Yuanlong Li, Linsen Dong, Xin Zhou, Yonggang Wen, Kyle Guan

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；model-based RL(abstract)；分类 cs.AI、cs.LG

Comments 13 pages

Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL

Anusha Nagabandi, Chelsea Finn, Sergey Levine

专题命中 模型式强化学习 ：model-based RL(title)；model-based reinforcement learning(abstract)；分类 cs.AI、cs.LG、cs.RO；predictive model(abstract)

Comments Project website: https://sites.google.com/berkeley.edu/onlineviameta

Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models

Vlad Sobal, Wancong Zhang, Kyunghyun Cho, Randall Balestriero, Tim G. J. Rudner, Yann LeCun

机构 * New York University（纽约大学） ； Genentech（基因泰克） ； Brown University（布朗大学） ； University of Toronto（多伦多大学） ； Meta – FAIR 纠错

专题命中 模型式强化学习 ：latent dynamics(title,abstract)；dynamics model(title,abstract)；分类 cs.LG

Comments Project web page: https://latent-planning.github.io/

Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning

Kimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, Jinwoo Shin

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；dynamics model(title,abstract)；分类 cs.LG

Comments Accepted in ICML2020. First two authors contributed equally, website: https://sites.google.com/view/cadm code: https://github.com/younggyoseo/CaDM

AlphaClifford: Efficient Clifford Synthesis and Transpilation with Model-based RL

AlphaClifford：基于模型强化学习的高效Clifford电路综合与 transpilation

Daniele Lizzio Bosco, Jacopo Cossio, Carla Piazza, Giuseppe Serra

专题命中 模型式强化学习 ：model-based RL(title,abstract)；model-based reinforcement learning(abstract)；分类 cs.AI

AI总结 本研究提出基于模型强化学习的AlphaClifford框架，用于高效综合Clifford电路，在总门数和CNOT门数上优于现有方法，还可用于硬件约束 transpilation及Clifford+T流程优化，为量子编译提供可扩展途径。

Comments Accepted manuscript to appear in the proceedings of the IEEE International Conference on Quantum Computing and Engineering (QCE 2026). 11 pages, 3 figures

Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model

通过学习深度逆动力学模型实现仿真到现实世界的迁移

Paul Christiano, Zain Shah, Igor Mordatch, Jonas Schneider, Trevor Blackwell, Joshua Tobin, Pieter Abbeel, Wojciech Zaremba

专题命中 模型式强化学习 ：world model(abstract)；dynamics model(title,abstract)；world model(abstract)；分类 cs.AI、cs.LG、cs.RO

AI总结 本文提出通过学习深度逆动力学模型，在仿真与现实世界之间实现控制策略的迁移，解决仿真与现实差异导致的性能下降问题。

First Order Model-Based RL through Decoupled Backpropagation

Joseph Amigo, Rooholla Khorrambakht, Elliot Chane-Sane, Nicolas Mansard, Ludovic Righetti

机构 * Machines in Motion Laboratory, New York University, USA（纽约大学运动机器实验室） ； LAAS-CNRS, Université de Toulouse, CNRS, Toulouse, France（图卢兹大学LAAS-CNRS） ； Artificial and Natural Intelligence Toulouse Institute, Toulouse, France（图卢兹人工智能与自然智能研究所） 纠错

专题命中 模型式强化学习 ：model-based RL(title,abstract)；分类 cs.AI、cs.LG、cs.RO；dynamics model(abstract)

Comments CoRL 2025. Project website: https://machines-in-motion.github.io/DMO/

Temporal Distance-aware Transition Augmentation for Offline Model-based Reinforcement Learning

Dongsu Lee, Minhae Kwon

机构 * Carnegie Mellon University, Pittsburgh, USA（卡内基梅隆大学） ； Department of Intelligent Semiconductors, Soongsil University, Seoul, South Korea（智能半导体系，顺斯大学） 纠错

专题命中 模型式强化学习 ：model-based reinforcement learning(title)；model-based RL(abstract)；分类 cs.AI、cs.LG、cs.RO；dynamics model(abstract)

Comments 2025 ICML

The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning

Moritz Schneider, Robert Krug, Narunas Vaskevicius, Luigi Palmieri, Joschka Boedecker

专题命中 模型式强化学习 ：model-based reinforcement learning(title)；model-based RL(abstract)；分类 cs.AI、cs.LG、cs.CV；dynamics model(abstract)

Comments Published at the 38th Conference on Neural Information Processing Systems (NeurIPS 2024). Project page: https://schneimo.com/pvr4mbrl/

Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation

Taehyun Hwang, Min-hwan Oh

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；model-based RL(abstract)；分类 cs.LG

Comments Accepted in AAAI 2023 (Main Technical Track)

Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds

Zhiyong Wang, Dongruo Zhou, John C. S. Lui, Wen Sun

专题命中 模型式强化学习 ：model-based RL(title,abstract)；model-based reinforcement learning(abstract)；分类 cs.LG

Optimization of Pressure Management Strategies for Geological CO2 Sequestration Using Surrogate Model-based Reinforcement Learning

Jungang Chen, Eduardo Gildin, Georgy Kompantsev

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；latent dynamics(abstract)；simulation model(abstract)

Comments 23 pages, 10 figures

Journal ref International Journal of Greenhouse Gas Control, Volume 138, 2024, 104262,

Enhancing Analogical Reasoning in the Abstraction and Reasoning Corpus via Model-Based RL

Jihwan Lee, Woochang Sim, Sejin Kim, Sundong Kim

专题命中 模型式强化学习 ：model-based RL(title,abstract)；model-based reinforcement learning(abstract)；分类 cs.AI

Comments Accepted to IJCAI 2024 IARML Workshop

Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption

Chenlu Ye, Jiafan He, Quanquan Gu, Tong Zhang

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；model-based RL(abstract)；分类 cs.LG

SAM-RL: Sensing-Aware Model-Based Reinforcement Learning via Differentiable Physics-Based Simulation and Rendering

Jun Lv, Yunhai Feng, Cheng Zhang, Shuang Zhao, Lin Shao, Cewu Lu

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；分类 cs.AI、cs.LG、cs.CV

Comments Accepted to Robotics: Science and Systems (RSS) 2023

On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning

Philipp Becker, Gerhard Neumann

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；model-based RL(abstract)；分类 cs.LG

Comments Published in TMLR, October 2022

Model-Based Reinforcement Learning with SINDy

Rushiv Arora, Bruno Castro da Silva, Eliot Moss

专题命中 模型式强化学习 ：model-based reinforcement learning(title)；model-based RL(abstract)；分类 cs.AI、cs.LG、cs.RO；dynamics model(abstract)

Comments 8 pages, 1 figure, 1 table, 1 algorithm, presented at the Decision Awareness in Reinforcement Learning workshop held at the International Conference on Machine Learning, 22 July 2022, Baltimore MD, USA

A Survey on Model-based Reinforcement Learning

Fan-Ming Luo, Tian Xu, Hang Lai, Xiong-Hui Chen, Weinan Zhang, Yang Yu

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；environment model(abstract)；分类 cs.LG

Multi-Objective Model-based Reinforcement Learning for Infectious Disease Control

Runzhe Wan, Xinyu Zhang, Rui Song

专题命中 模型式强化学习 ：model-based reinforcement learning(title,abstract)；environment model(abstract)；分类 cs.LG