Framing Relevance for Safety-Critical Autonomous Systems

TL;DR

This paper proposes a formal method to identify relevant information for safety-critical autonomous systems, enabling them to focus on essential data for effective decision-making during missions.

Contribution

It introduces a formal approach to determine relevance of information for autonomous systems, enhancing their ability to build appropriate world views for mission success.

Findings

Framework for relevance determination in autonomous systems

Improved decision-making efficiency in safety-critical contexts

Enhanced focus on mission-critical information

Abstract

We are in the process of building complex highly autonomous systems that have build-in beliefs, perceive their environment and exchange information. These systems construct their respective world view and based on it they plan their future manoeuvres, i.e., they choose their actions in order to establish their goals based on their prediction of the possible futures. Usually these systems face an overwhelming flood of information provided by a variety of sources where by far not everything is relevant. The goal of our work is to develop a formal approach to determine what is relevant for a safety critical autonomous system at its current mission, i.e., what information suffices to build an appropriate world view to accomplish its mission goals.