Schedule Explainer: An Argumentation-Supported Tool for Interactive Explanations in Makespan Scheduling

Kristijonas Čyras*, Myles Lee, Dimitrios Letsios

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

5 Citations (Scopus)

Abstract

Scheduling is a fundamental optimisation problem that has a wide range of practical applications. Mathematical formulations of scheduling problems allow for development of efficient solvers. Yet, the same mathematical intricacies often make solvers black-boxes: their outcomes are hardly explainable and interactive even to experts, let alone lay users. Still, in real-world applications as well as research environments, lay users and experts likewise require a means to understand why a schedule is reasonable and what would happen with different schedules. Building upon a recently proposed approach to argumentation-supported explainable scheduling, we present a tool, Schedule Explainer, that provides interactive explanations in makespan scheduling easily and with clarity.

Original languageEnglish
Title of host publicationExplainable and Transparent AI and Multi-Agent Systems - 3rd International Workshop, EXTRAAMAS 2021, Revised Selected Papers
EditorsDavide Calvaresi, Amro Najjar, Michael Winikoff, Kary Främling
PublisherSpringer Science and Business Media Deutschland GmbH
Pages243-259
Number of pages17
ISBN (Print)9783030820169
DOIs
Publication statusPublished - 2021
Event3rd International Workshop on Explainable, Transparent AI and Multi-Agent Systems, EXTRAAMAS 2021 - Virtual, Online
Duration: 3 May 20217 May 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12688 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Workshop on Explainable, Transparent AI and Multi-Agent Systems, EXTRAAMAS 2021
CityVirtual, Online
Period3/05/20217/05/2021

Keywords

  • Explainability
  • Implementation
  • Scheduling

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