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Steps Towards Satisficing Distributed Dynamic Team Trust

Edmund R. Hunt, Chris Baber, Mehdi Sobhani, Sanja Milivojevic, Sagir Yusuf, Mirco Musolesi, Patrick Waterson, Sally Maynard

TL;DR

The paper addresses the challenge of defining and measuring trust in dynamic, distributed human-robot teams by proposing an interpretable trust framework built around a Ladder of Trust and a three-element model of trust: Capability, Predictability, and Integrity. It operationalizes trust through Bayesian Belief Networks within a Cognitive Work Analysis-derived mission structure and a distributed situation awareness approach, enabling satisficing decisions as missions unfold. Key contributions include a metrics suite linking observed actions to goals and values, a context-aware integrity/reputation mechanism, and a practical experimental plan using AR-tag-enabled rover teams to study trust dynamics under competing selfish and team goals. The work aims to guide both humans and robots to adapt their trust assessments in real-time, supporting safer and more effective collaboration in mission-critical settings.

Abstract

Defining and measuring trust in dynamic, multiagent teams is important in a range of contexts, particularly in defense and security domains. Team members should be trusted to work towards agreed goals and in accordance with shared values. In this paper, our concern is with the definition of goals and values such that it is possible to define 'trust' in a way that is interpretable, and hence usable, by both humans and robots. We argue that the outcome of team activity can be considered in terms of 'goal', 'individual/team values', and 'legal principles'. We question whether alignment is possible at the level of 'individual/team values', or only at the 'goal' and 'legal principles' levels. We argue for a set of metrics to define trust in human-robot teams that are interpretable by human or robot team members, and consider an experiment that could demonstrate the notion of 'satisficing trust' over the course of a simulated mission.

Steps Towards Satisficing Distributed Dynamic Team Trust

TL;DR

The paper addresses the challenge of defining and measuring trust in dynamic, distributed human-robot teams by proposing an interpretable trust framework built around a Ladder of Trust and a three-element model of trust: Capability, Predictability, and Integrity. It operationalizes trust through Bayesian Belief Networks within a Cognitive Work Analysis-derived mission structure and a distributed situation awareness approach, enabling satisficing decisions as missions unfold. Key contributions include a metrics suite linking observed actions to goals and values, a context-aware integrity/reputation mechanism, and a practical experimental plan using AR-tag-enabled rover teams to study trust dynamics under competing selfish and team goals. The work aims to guide both humans and robots to adapt their trust assessments in real-time, supporting safer and more effective collaboration in mission-critical settings.

Abstract

Defining and measuring trust in dynamic, multiagent teams is important in a range of contexts, particularly in defense and security domains. Team members should be trusted to work towards agreed goals and in accordance with shared values. In this paper, our concern is with the definition of goals and values such that it is possible to define 'trust' in a way that is interpretable, and hence usable, by both humans and robots. We argue that the outcome of team activity can be considered in terms of 'goal', 'individual/team values', and 'legal principles'. We question whether alignment is possible at the level of 'individual/team values', or only at the 'goal' and 'legal principles' levels. We argue for a set of metrics to define trust in human-robot teams that are interpretable by human or robot team members, and consider an experiment that could demonstrate the notion of 'satisficing trust' over the course of a simulated mission.
Paper Structure (11 sections, 2 equations, 4 figures, 1 table)

This paper contains 11 sections, 2 equations, 4 figures, 1 table.

Table of Contents

  1. Introduction
  2. Principles, Values and Goals
  3. Values in Human-Robot Teams
  4. Trust Specification
  5. Motivating Use-Case
  6. Defining Metrics for Trust
  7. Integrity, Reputation and Values
  8. Trust and Distributed Situation Awareness
  9. Illustrating a Ladder of Trust in the Experimental Environment
  10. Discussion
  11. Acknowledgements

Figures (4)

  • Figure 1: Alignment of goals and principles between humans and robots is possible; expressing 'values' in contextualized goal priorities remains the province of human actors.
  • Figure 2: Agent 1’s trust in Agent 2, $T_{12}$, depends on its running estimates of Agent 2’s capability, predictability and integrity; these are contextualized by the local situation.
  • Figure 3: A ‘Leo Rover’ robot equipped with 2D LiDAR and built-in front facing camera, which can scan ARTags.
  • Figure 4: A teammate's Bayesian Belief Network (BBN) based on their observation of Agent 1's choice of action in a context.