Model-Based Planning

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38 papers in the last four weeks, up 192% on the four weeks before. 0.4% of all new papers.

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Latest papers 166

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The Global Neural World Model: Spatially Grounded Discrete Topologies for Action-Conditioned Planning
Apr 17, 2026Noureddine KermicheWorld Model Learning World Model-Based Planning
Western Digital Corporation, Irvine, CA, USA
Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning
Apr 16, 2026Jean-Bastien Grill, Michal Valko, Rémi MunosMarkov Decision Processes Markov Models
SequeL team, INRIA Lille - Nord Europe, France · Google DeepMind, UK∗
World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems
Apr 16, 2026Runze Li, Hongyin Zhang, Junxi Jin +5Vision-Language-Action Models Model-Based Planning
Westlake University Hangzhou, China · Nanjing University Suzhou Campus, 1520 Taihu Avenue, Suzhou, China
Beyond State Consistency: Behavior Consistency in Text-Based World Models
Apr 15, 2026Youling Huang, Guanqiao Chen, Junchi Yao +8World Models World Model Learning
Dalian University of Technology · Microsoft · MBZUAI +1
Grounded World Model: Latent Planning with Language Goals
Apr 13, 2026Quanyi Li, Lan Feng, Haonan Zhang +4Zero-Shot Robotic Manipulation World Models for Robotics
EPFL · NUS
Object Search in Partially-Known Environments via LLM-informed Model-based Planning and Prompt Selection
Mar 25, 2026Abhishek Paudel, Abhish Khanal, Raihan I. Arnob +2Large Language Model-Based Robot Planning Model-Based Planning
Department of Computer Science at George Mason University, Fairfax, Virginia, USA.
Algorithms for Deciding the Safety of States in Fully Observable Non-deterministic Problems: Technical Report
Mar 16, 2026Johannes Schmalz, Chaahat JainPolicy Iteration Model-Based Planning
Saarland University, Germany
MoMaStage: Skill-State Graph Guided Planning and Closed-Loop Execution for Long-Horizon Indoor Mobile Manipulation
Mar 9, 2026Chenxu Li, Zixuan Chen, Yetao Li +5Long-Horizon Robotic Manipulation Mobile Manipulation
All authors are with Nanjing University, China.
Relating Reinforcement Learning to Dynamic Programming-Based Planning
Mar 8, 2026Filip V. Georgiev, Kalle G. Timperi, Başak Sakçak +1Markov Decision Processes Dynamic Programming
Center for Applied Computing, Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland · Dept. of Advanced Computing Sciences, Maastricht University, the Netherlands
NavDreamer: Video Models as Zero-Shot 3D Navigators
Feb 10, 2026Xijie Huang, Weiqi Gai, Tianyue Wu +5Vision-Language Navigation Model-Based Planning
Zhejiang University · Differential Robotics · Beihang University
Textual Planning with Explicit Latent Transitions
Feb 4, 2026Eliezer Shlomi, Ido Levy, Eilam Shapira +6Latent Dynamics Modeling LLM Planning
Technion – Israel Institute of Technology, Haifa, Israel · IBM, Haifa, Israel.
Imagine-then-Plan: Agent Learning from Adaptive Lookahead with World Models
Jan 13, 2026Youwei Liu, Jian Wang, Hanlin Wang +2World Model-Based Planning Model-Based Planning
Central South University · Department of Computing, The Hong Kong Polytechnic University · College of Computer Science, Sichuan University
MobileDreamer: Generative Sketch World Model for GUI Agent
Jan 7, 2026Yilin Cao, Yufeng Zhong, Zhixiong Zeng +6Mobile GUI Automation World Model Learning
State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences · Meituan · School of Artificial Intelligence, University of Chinese Academy of Sciences
Robust and Efficient MuJoCo-based Model Predictive Control via Web of Affine Spaces Derivatives
Dec 24, 2025Chen Liang, Daniel RakitaRobotic Control Model Predictive Control
Department of Computer Science, Yale University, New Haven, CT 06520, USA
CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents
Nov 4, 2025Jiayu Liu, Cheng Qian, Zhaochen Su +4LLM Planning LLM Agent Evaluation
The Hong Kong University of Science and Technology · University of Illinois Urbana-Champaign · Tsinghua University
Captivity-Escape Games as a Means for Safety in Online Motion Generation
Jun 2, 2025Christopher Bohn, Manuel Hess, Sören HohmannTrajectory Generation Safety-Critical Control
Institute of Control Systems, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany

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The Global Neural World Model: Spatially Grounded Discrete Topologies for Action-Conditioned Planning

Noureddine Kermiche

Western Digital Corporation, Irvine, CA, USA

World Model Learning World Model-Based Planning Joint-Embedding Predictive Architecture Action-Conditioned World Models Model-Based Planning Topological Representation Learning

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We present the Global Neural World Model (GNWM), a self-stabilizing framework that achieves topological quantization through balanced continuous entropy constraints. Operating as a continuous, action-conditioned Joint-Embedding Predictive Architecture (JEPA), the GNWM maps environments onto a discrete 2D grid, enforcing translational equivariance without pixel-level reconstruction. Our results show this architecture prevents manifold drift during autoregressive rollouts by using grid ``snapping'' as a native error-correction mechanism. Furthermore, by training via maximum entropy exploration (random walks), the model learns generalized transition dynamics rather than memorizing specific expert trajectories. We validate the GNWM across passive observation, active agent control, and abstract sequence regimes, demonstrating its capacity to act not just as a spatial physics simulator, but as a causal discovery model capable of organizing continuous, predictable concepts into structured topological maps.

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