GaP：面向变分自动化任务的 Graph-as-Policy 多智能体自学习框架
GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks
研究者提出 Graph-as-Policy（GaP），一种多智能体编程框架，可从模块化开放机器人技能库 MORSL 生成包含感知、规划和控制节点的有向计算图，用于处理物体几何与位姿变化较大的变分自动化（VA）任务。
Authors:Kaiyuan Chen, Shuangyu Xie, Letian Fu, Justin Yu, William Pacini, Sandeep Bajamahal, Hudson Kim, Jaimyn Drake, Daehwa Kim, Haoru Xue, Jonathan Francis, Christian Juette, Peter Schaldenbrand, Muhammet Yunus Seker, Ruwan Wickramarachchi, Uksang Yoo, Guanzhi Wang, Adithyavairavan Murali, Balakumar Sundaralingam, S. Shankar Sastry, Yuke Zhu, Linxi "Jim" Fan, Spencer Huang, Ken Goldberg
Abstract:For robots to work reliably in commercial and industrial applications, recent advances in agentic coding systems have potential to combine interpretable robot programming with the open-world adaptability of model-free policies. We focus on "Variational Automation" (VA), a class of tasks that have larger variations in object geometry and pose than fixed automation. Model-free policies often struggle to close the reliability gap for VA tasks, which must be executed persistently and reliably in commercial and industrial applications. Motivated by prior work on Task and Motion Planning (TAMP) and the Robot Operating System (ROS), we introduce Graph-as-Policy (GaP), a multi-agent coding harness that generates directed computation graphs with perception, planning, and control nodes from a Modular Open Robot Skill Library (MORSL). GaP generates an internal simulation environment to rehearse task instances with different graphs in parallel to iteratively refine the graph structure and parameters to improve success rates and throughput. Evaluation with 8 new open VA task benchmarks, 4 in simulation and 4 in real-world, suggests that GaP can achieve success rates that significantly outperform baselines. Details, code, and data: this https URL
| Subjects: | Robotics (cs.RO); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG) |
| Cite as: | arXiv:2607.05369 [cs.RO] |
| (or arXiv:2607.05369v2 [cs.RO] for this version) | |
| https://doi.org/10.48550/arXiv.2607.05369 arXiv-issued DOI via DataCite |
Submission history
From: Jaimyn Drake [view email]
[v1]
Mon, 6 Jul 2026 17:47:31 UTC (6,853 KB)
[v2]
Fri, 23 Oct 2026 17:46:52 UTC (4,428 KB)
来源：arXiv cs.AI · arxiv.org