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Argument Schemes and a Dialogue System for Explainable Planning

journal contribution
posted on 2024-03-01, 12:43 authored by Quratul-ain Mahesar, Marc HanheideMarc Hanheide, Simon ParsonsSimon Parsons

Artificial Intelligence (AI) is being increasingly deployed in practical applications. However, there is a major concern whether AI systems will be trusted by humans. In order to establish trust in AI systems, there is a need for users to understand the reasoning behind their solutions. Therefore, systems should be able to explain and justify their output. Explainable AI Planning (XAIP) is a field that involves explaining the outputs, i.e., solution plans produced by AI planning systems to a user. The main goal of a plan explanation is to help humans understand reasoning behind the plans that are produced by the planners. In this paper, we propose an argument scheme-based approach to provide explanations in the domain of AI planning. We present novel argument schemes to create arguments that explain a plan and its key elements; and a set of critical questions that allow interaction between the arguments and enable the user to obtain further information regarding the key elements of the plan. Furthermore, we present a novel dialogue system using the argument schemes and critical questions for providing interactive dialectical explanations.

Funding

Trust in Human-Machine Partnership

UK Research and Innovation

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History

School affiliated with

  • School of Computer Science (Research Outputs)

Publication Title

ACM Transactions on Intelligent Systems and Technology

Volume

14

Issue

5

Pages/Article Number

Article no. 89, pp 1–25

Publisher

Association for Computing Machinery (ACM)

ISSN

2157-6904

eISSN

2157-6912

Date Submitted

2023-08-18

Date Accepted

2023-06-27

Date of First Publication

2023-01-01

Date of Final Publication

2023-10-01

Date Document First Uploaded

2023-08-01

ePrints ID

55636

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    University of Lincoln (Research Outputs)

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