Incorporating a 'ladder of trust' into dynamic Allocation of Function in Human-Autonomous Agent Collectives
Chris Baber, Patrick Waterson, Sanja Milivojevic, Sally Maynard,, Edmund R. Hunt, Sagir Yusuf

TL;DR
This paper proposes a dynamic function allocation method in human-autonomous teams based on a 'ladder of trust' that adjusts team roles according to individual trust scores derived from situational understanding and performance, enhancing team cohesion and effectiveness.
Contribution
It introduces a novel trust-based framework for dynamic function allocation in human-autonomous collectives, considering ethical, legal, and moral constraints.
Findings
Trust scores influence role assignment decisions.
System-level perspective improves team adaptability.
Trust-based allocation enhances team performance.
Abstract
A major, ongoing social transition is the inclusion of autonomous agents into human organizations. For example, in defence and security applications, robots may be used alongside human operatives to reduce risk or add capability. But a key barrier to the transition to successful human-autonomous agent collectives is the need for sufficient trust between team members. A critical enabling factor for this trust will be a suitably designed dynamic allocation of function (AoF). We consider AoF in terms of a 'ladder of trust' (from low to high) with individual team members adjusting trust in their teammates based on variation in 'score' over time. The score is derived by the ability of team member to perceive and understand its situation based on the gathered information and act to acheive team or self goals. Combining these trust scores gives a system-level perspective on how AoF might be…
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Taxonomy
TopicsCognitive Science and Mapping · Embodied and Extended Cognition · Multi-Agent Systems and Negotiation
