Multi-Objective Adaptation After Deployment: A Position on World Models for Remote Robot Teams
Multi-Objective Adaptation After Deployment: A Position on World Models for Remote Robot Teams
This paper argues that world models merit investigation for enabling autonomous robot teams deployed in remote environments to adapt to changes in conditions, hardware, or mission objectives without physically testing every candidate policy. The authors identify key research priorities including validating predicted versus realized performance and incorporating shared information into world models to support coordinated team adaptation.
The authors propose investigating world models for post-deployment multi-objective adaptation in remote robot teams, arguing they could enable policy re-evaluation without physical execution if predicted performance matches realized outcomes; however, the approach is noted as largely untested in this domain.
Source: arXiv Robotics — research abstracts · Read original article ↗
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Source：arXiv Robotics — research abstracts · arxiv.org