arXiv：cs.AI· Changbai Li, Sirui Li, Yichen Yang, Tongfei Chen, Zichao Feng, Shuwei Shao, Huobin Tan·· 6 小时前AI 评分31
世界模型规划需要多少预算？SufficientPlan 减少搜索与计算开销
How Much Planning Is Enough? Reducing Search and Computation in World-Model Planning
AI 导读
研究者提出 SufficientPlan 部署框架，无需修改预训练世界模型或规划器，即可大幅削减决策时的动作搜索预算与规划延迟。
正文
Abstract:Visual world models enable goal-directed control through decision-time action search, but their deployment efficiency is often limited by conservatively large planning budgets. We show that competitive task performance can be achieved without agreement with the Full-budget action, that sufficient budgets vary across model--task pairs, and that iterative planners repeatedly encode solve-invariant context. To address these inefficiencies, we propose {SufficientPlan}, a simple deployment framework that requires no modification to pretrained world models or planner updates. Its {Paired Sequential Budget Certification (PSBC)} component uses paired closed-loop evidence to search for and certify a reduced model--task-specific budget within a predefined Full-performance tolerance. Its {Static-Context Reuse (SCR)} component caches observation and goal representations across search iterations while preserving candidate-dependent planning and selected actions. Experiments across multiple world-model backbones and visual-control tasks show that SufficientPlan substantially reduces search budgets and planning latency while maintaining competitive control performance.
| Subjects: | Robotics (cs.RO); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.08350 [cs.RO] |
| (or arXiv:2610.08350v1 [cs.RO] for this version) | |
| https://doi.org/10.48550/arXiv.2610.08350 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Changbai Li [view email]
[v1]
Tue, 6 Oct 2026 13:40:44 UTC (792 KB)
来源：arXiv：cs.AI · arxiv.org