An argumentation-based approach to generate domain-specific explanations

Nadin Kokciyan, Simon Parsons, Isabel Sassoon, Elizabeth Sklar, Sanjay Modgil

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In argumentation theory, argument schemes are constructs to generalise common patterns of reasoning; whereas critical questions (CQs) capture the reasons why argument schemes might not generate arguments. Argument schemes together with CQs are widely used to instantiate arguments; however when it comes to making decisions, much less attention has been paid to the attacks among arguments. This paper provides a high-level description of the key elements necessary for the formalisation of argumentation frameworks such as argument schemes and CQs. Attack schemes are then introduced to represent attacks among arguments, which enable the definition of domain-specific attacks. One algorithm is articulated to operationalise the use of schemes to generatean argumentation framework, and another algorithm to support decision making by generating domain-specific explanations. Such algorithms can then be used by agents to make recommendations and to provide explanations for humans. The applicability of this approach is demonstrated within the context of a medical case study.
Original languageEnglish
Title of host publicationMulti-Agent Systems and Agreement Technologies (EUMAS 2020)
PublisherSpringer
Number of pages18
ISBN (Electronic)978-3-030-66412-1
ISBN (Print)978-3-030-66411-4
DOIs
Publication statusPublished - 5 Jan 2021
Event17th European Conference on Multi-Agent Systems - Virtual Conference
Duration: 14 Sept 202015 Sept 2020
https://eumas2020.csd.auth.gr/eumas2020/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume12520
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th European Conference on Multi-Agent Systems
Abbreviated titleEUMAS 2020
CityVirtual Conference
Period14/09/2015/09/20
Internet address

Keywords / Materials (for Non-textual outputs)

  • Computational argumentation
  • Explainability
  • Human-agent systems

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