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Communicating Agent Intentions for Human-Agent Decision Making under Uncertainty

Published: 30 May 2023 Publication History

Abstract

Recent advances in visualisation technologies have opened up new possibilities for human-agent communication. For systems where agents use automated planning, visualisation of agent intentions, i.e., agent planned actions, can assist human understanding and decision making (e.g., deciding when human control is required or when it can be delegated to an agent). We are working in an application area, shipbuilding, where branched plans are often essential, due to the typical uncertainty experienced. Our focus is how best to communicate, using visualisation, the key information content of branched plans. It is important that such visualisations communicate the complexity and variety of the possible agent intentions i.e., executions, captured in a branched plan, whilst also connecting to the practitioner's understanding of the problem. Thus we utilise an approach to generate the complete branched plan, to be able to provide a full picture of its complexity, and a mechanism to select a subset of diverse traces that characterise the possible agent intentions. We have developed an interface which uses 3D visualisation to communicate details of these characterising execution traces. Using this interface, we conducted a study evaluating the impact of different modes of presentation on user understanding. Our results support our expectation that visualisation of branched plan characterising execution traces increases user understanding of agent intention and plan execution possibilities.

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Cited By

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  • (2024)On the Utility of External Agent Intention Predictor for Human-AI CoordinationProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3663222(2546-2548)Online publication date: 6-May-2024
  • (2024)Exploring Preferences in Human-Robot Navigation Plan Proposal RepresentationCompanion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610978.3640627(369-373)Online publication date: 11-Mar-2024

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  1. Communicating Agent Intentions for Human-Agent Decision Making under Uncertainty

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      cover image ACM Conferences
      AAMAS '23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems
      May 2023
      3131 pages
      ISBN:9781450394321
      • General Chairs:
      • Noa Agmon,
      • Bo An,
      • Program Chairs:
      • Alessandro Ricci,
      • William Yeoh

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      International Foundation for Autonomous Agents and Multiagent Systems

      Richland, SC

      Publication History

      Published: 30 May 2023

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      Author Tags

      1. explainable AI planning
      2. human-agent decision making
      3. virtual agents

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      Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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      View all
      • (2024)On the Utility of External Agent Intention Predictor for Human-AI CoordinationProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3663222(2546-2548)Online publication date: 6-May-2024
      • (2024)Exploring Preferences in Human-Robot Navigation Plan Proposal RepresentationCompanion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610978.3640627(369-373)Online publication date: 11-Mar-2024

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