Knowledge-Guided Manipulation Using Multi-Task Reinforcement Learning
This paper introduces Knowledge Graph based Massively Multi-task Model-based Policy Optimization (KG-M3PO), a framework for multi-task robotic manipulation in partially observable settings that unifies Perception, Knowledge, and Policy. The method augments egocentric vision with an online 3D scene graph that grounds open-vocabulary detections into a metric, relational representation. A dynamic-relation mechanism updates spatial, containment, and affordance edges at every step, and a graph neural
Record details
Published: 25 March 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy
Retrieved: 14 July 2026
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ethics.ai (25 March 2026), “Knowledge-Guided Manipulation Using Multi-Task Reinforcement Learning,” evidence record 6774, https://ethics.ai/record/6774 (originally published by arXiv).
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