世界模型

In-Context Planning with Latent Temporal Abstractions

基于潜在时间抽象的上下文规划

Baiting Luo, Yunuo Zhang, Nathaniel S. Keplinger, Samir Gupta, Abhishek Dubey, Ayan Mukhopadhyay

机构 * Vanderbilt University（范德比大学） ； William & Mary（威廉与玛丽学院） 纠错

专题命中 仿真与规划 ：latent dynamics(abstract)；分类 cs.AI、cs.LG；dynamics model(abstract)

AI总结 I-TAP通过学习离散时间抽象空间，实现高效且鲁棒的上下文规划，在部分可观测和随机动态环境中表现优异。

Improving planning and MBRL with temporally-extended actions

Palash Chatterjee, Roni Khardon

机构 * Indiana University（印第安纳大学） 纠错

专题命中 仿真与规划 ：model-based reinforcement learning(abstract)；分类 cs.AI、cs.LG、cs.RO

Comments NeurIPS 2025. For project website, see https://pecey.github.io/MBRL-with-TEA/

Distilling Reinforcement Learning Algorithms for In-Context Model-Based Planning

Jaehyeon Son, Soochan Lee, Gunhee Kim

机构 * Seoul National University（首尔大学） ； LG AI Research（LG AI研究院） 纠错

专题命中 仿真与规划 ：model-based RL(abstract)；分类 cs.AI、cs.LG；dynamics model(abstract)

Comments ICLR 2025

Efficient Multi-agent Reinforcement Learning by Planning

Qihan Liu, Jianing Ye, Xiaoteng Ma, Jun Yang, Bin Liang, Chongjie Zhang

专题命中 仿真与规划 ：model-based reinforcement learning(abstract)；分类 cs.AI、cs.LG、cs.MA

Comments ICLR2024

AutoNeRF: Training Implicit Scene Representations with Autonomous Agents

Pierre Marza, Laetitia Matignon, Olivier Simonin, Dhruv Batra, Christian Wolf, Devendra Singh Chaplot

专题命中 仿真与规划 ：environment model(abstract)；分类 cs.LG、cs.CV、cs.RO

Planning with Diffusion for Flexible Behavior Synthesis

Michael Janner, Yilun Du, Joshua B. Tenenbaum, Sergey Levine

专题命中 仿真与规划 ：model-based reinforcement learning(abstract)；分类 cs.AI、cs.LG；dynamics model(abstract)

Comments ICML 2022 (long talk). Project page and code at https://diffusion-planning.github.io/

Double Check Your State Before Trusting It: Confidence-Aware Bidirectional Offline Model-Based Imagination

Jiafei Lyu, Xiu Li, Zongqing Lu

专题命中 仿真与规划 ：model-based RL(abstract)；分类 cs.AI、cs.LG；dynamics model(abstract)

Comments NeurIPS 2022

A Unifying Framework for Reinforcement Learning and Planning

Thomas M. Moerland, Joost Broekens, Aske Plaat, Catholijn M. Jonker

专题命中 仿真与规划 ：model-based RL(abstract)；分类 cs.AI、cs.LG、cs.RO

Learning Space Partitions for Path Planning

Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian

专题命中 仿真与规划 ：model-based RL(abstract)；分类 cs.AI、cs.LG、cs.RO

Journal ref NeurIPS 2021

DeepKoCo: Efficient latent planning with a task-relevant Koopman representation

Bas van der Heijden, Laura Ferranti, Jens Kober, Robert Babuska

专题命中 仿真与规划 ：latent dynamics(abstract)；分类 cs.LG、cs.CV、cs.RO

Predictive Control Using Learned State Space Models via Rolling Horizon Evolution

Alvaro Ovalle, Simon M. Lucas

专题命中 仿真与规划 ：model-based reinforcement learning(abstract)；分类 cs.AI、cs.LG；predictive model(abstract)

Comments Accepted at the Bridging the Gap Between AI Planning and Reinforcement Learning (PRL) Workshop at ICAPS 2021

Improving the Exploration of Deep Reinforcement Learning in Continuous Domains using Planning for Policy Search

Jakob J. Hollenstein, Erwan Renaudo, Matteo Saveriano, Justus Piater

专题命中 仿真与规划 ：model-based reinforcement learning(abstract)；分类 cs.LG、cs.RO；simulation model(abstract)

Regularizing Model-Based Planning with Energy-Based Models

Rinu Boney, Juho Kannala, Alexander Ilin

专题命中 仿真与规划 ：model-based reinforcement learning(abstract)；分类 cs.LG、cs.RO；dynamics model(abstract)

Comments Conference on Robot Learning 2019

Partially Observable Planning and Learning for Systems with Non-Uniform Dynamics

Nicholas Collins, Hanna Kurniawati

专题命中 仿真与规划 ：environment model(abstract)；分类 cs.AI、cs.LG、cs.RO

Exploring Model-based Planning with Policy Networks

Tingwu Wang, Jimmy Ba

专题命中 仿真与规划 ：model-based reinforcement learning(abstract)；分类 cs.AI、cs.LG、cs.RO

Comments 8 pages, 7 figures

Dyna Planning using a Feature Based Generative Model

Ryan Faulkner, Doina Precup

专题命中 仿真与规划 ：environment model(abstract)；分类 cs.AI、cs.LG、cs.CV

Comments 8 pages, 7 figures

Journal ref 24th Annual Proceedings of the Advances in Neural Information Processing Systems (2010) pp. 1-9

LLM Agents Perform Controlled Experiments Using Simulation Models

大语言模型智能体使用模拟模型开展对照实验

Yuchen Xia, Michael Weyrich, Nasser Jazdi, Johannes Stümpfle, Johannes Sigel, Akshay Narla, Gavin K. Reynolds, Anna Jawor-Baczynska, Pol Llopart

机构 * Institute for Industrial Automation and Software Engineering（工业自动化与软件工程研究所） ； University of Stuttgart（斯图加特大学） ； AstraZeneca（阿斯利康） 纠错

专题命中 仿真与规划 ：simulation model(title,abstract)；分类 cs.AI、cs.MA

AI总结 本研究提出多智能体框架，将LLM与高保真模拟模型结合，使LLM智能体可开展制药工艺设计的对照实验，生成更具体可操作的优化建议，在工业场景中表现更优。

Comments Accepted at the 31st IEEE International Conference on Emerging Technologies and Factory Automation ETFA 2026

Agentic Calibration of Grey-Box Simulation Models: An LLM-Driven Alternative

灰箱仿真模型的智能校准：一种由大语言模型驱动的替代方法

David Gómez-Guillén, Mireia Diaz, Josep Lluis Arcos, Jesús Cerquides

机构 * Catalan Institute of Oncology-IDIBELL（加泰罗尼亚肿瘤研究所-IDIBELL） ； Autonomous University of Barcelona（巴塞罗那自治大学） ； Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública（国家公共卫生与流行病学网络生物医学研究中心） ； Artificial Intelligence Research Institute, IIIA-CSIC（人工智能研究所，西班牙科学研究委员会-人工智能研究所） 纠错

专题命中 仿真与规划 ：simulation model(title,abstract)；分类 cs.AI、cs.LG

AI总结 研究灰箱仿真模型校准问题，提出用大语言模型作优化器的智能校准方法，在肛门癌仿真模型上评估，结果表明该方法在减少模型评估次数上有优势，虽迭代推理时间增加，但可审计和解释，适用于仿真时间占主导的情况。

Comments Manuscript: 19 pages, 2 figures. Appendix: 11 pages, 1 figure

Generative Digital Twins: Vision-Language Simulation Models for Executable Industrial Systems

生成数字孪生：用于可执行工业系统的视觉-语言模拟模型

YuChe Hsu, AnJui Wang, TsaiChing Ni, YuanFu Yang

机构 * Institute of Artificial Intelligence Innovation（人工智能创新研究所） 纠错

专题命中 仿真与规划 ：simulation model(title,abstract)；分类 cs.AI、cs.CV

AI总结 本文提出视觉-语言模拟模型VLSM，通过统一视觉与文本理解，实现从布局草图和自然语言提示生成可执行的工业模拟代码，建立首个大规模生成数字孪生数据集并提出三个专用评估指标。

Comments 10 pages, 9 figures

A Benchmark Time Series Dataset for Semiconductor Fabrication Manufacturing Constructed using Component-based Discrete-Event Simulation Models

Vamsi Krishna Pendyala, Hessam S. Sarjoughian, Bala Potineni, Edward J. Yellig

专题命中 仿真与规划 ：simulation model(title,abstract)；分类 cs.AI、cs.LG

CoSMo: a Framework to Instantiate Conditioned Process Simulation Models

Rafael S. Oyamada, Gabriel M. Tavares, Sylvio Barbon Junior, Paolo Ceravolo

专题命中 仿真与规划 ：simulation model(title,abstract)；分类 cs.AI、cs.LG

A Comprehensive Modeling Approach for Crop Yield Forecasts using AI-based Methods and Crop Simulation Models

Renato Luiz de Freitas Cunha, Bruno Silva, Priscilla Barreira Avegliano

专题命中 仿真与规划 ：simulation model(title,abstract)；分类 cs.AI、cs.LG

Efficient Calibration of Multi-Agent Simulation Models from Output Series with Bayesian Optimization

Yuanlu Bai, Henry Lam, Svitlana Vyetrenko, Tucker Balch

专题命中 仿真与规划 ：simulation model(title)；分类 cs.AI、cs.LG、cs.MA

Comments This paper has been accepted and will be published in ICAIF 2022 proceedings

Facilitating automated conversion of scientific knowledge into scientific simulation models with the Machine Assisted Generation, Calibration, and Comparison (MAGCC) Framework

Chase Cockrell, Scott Christley, Gary An

专题命中 仿真与规划 ：simulation model(title,abstract)；分类 cs.AI、cs.LG

Comments 20 Pages, 8 Figures, 5 Tables

An Improved Simulation Model for Pedestrian Crowd Evacuation

Danial A. Muhammed, Tarik A. Rashid, Abeer Alsadoon, Nebojsa Bacanin, Polla Fattah, Mokhtar Mohammadi, Indradip Banerjee

专题命中 仿真与规划 ：simulation model(title,abstract)；分类 cs.AI、cs.MA

Comments 15 pages, accepted in Mathematics, MDPI, 2020

Agent-based Simulation Model and Deep Learning Techniques to Evaluate and Predict Transportation Trends around COVID-19

Ding Wang, Fan Zuo, Jingqin Gao, Yueshuai He, Zilin Bian, Suzana Duran Bernardes, Chaekuk Na, Jingxing Wang, John Petinos, Kaan Ozbay, Joseph Y. J. Chow, Shri Iyer, Hani Nassif, Xuegang Jeff Ban

专题命中 仿真与规划 ：simulation model(title,abstract)；分类 cs.CV、cs.MA

A Simulation Model for Pedestrian Crowd Evacuation Based on Various AI Techniques

Danial A. Muhammed, Soran A. M. Saeed, Tarik A. Rashid

专题命中 仿真与规划 ：simulation model(title,abstract)；分类 cs.AI、cs.MA

Comments 10 pages

Journal ref Revue d'Intelligence Artificielle, 2019

Simulation Model of Two-Robot Cooperation in Common Operating Environment

V. Ya. Vilisov, B. Yu. Murashkin, A. I. Kulikov

专题命中 仿真与规划 ：simulation model(title,abstract)；分类 cs.AI、cs.RO

Comments 6 pages, 6 figures

A Work Zone Simulation Model for Travel Time Prediction in a Connected Vehicle Environment

Xuejin Wen

专题命中 仿真与规划 ：simulation model(title,abstract)；分类 cs.LG、cs.MA

Towards a Self-Organized Agent-Based Simulation Model for Exploration of Human Synaptic Connections

Önder Gürcan, Carole Bernon, Kemal S. Türker

专题命中 仿真与规划 ：simulation model(title,abstract)；分类 cs.AI、cs.LG

Comments 4 pages, 1 figure, 2nd Computer Science Student Workshop