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Author Audun Stolpe; Jo Hannay
Title On the Adaptive Delegation and Sequencing of Actions Type Conference Article
Year 2021 Publication ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2021
Volume Issue Pages (down) 28-39
Keywords Decision support, AI Planning, Delegation, Sequencing, Adaptivity, Cognitive processes
Abstract Information systems support to crisis response and management relies crucially on presenting actionable information in a manner that supports cognitive processes, and does not overwhelm them. We outline how AI Planning can be used viably to support the \emph{delegation and sequencing} of tasks. The idea is to use standard operating procedures as initial specifications of plans in terms of actors, actions and delegation rules. When expressed in the AI planning language \textit{Answer set Programming} (ASP), machine reasoning can be used in a \textit{pre-incident review} to display relevant delegation and sequencing inherent in a plan. % together with measures of goal achievement. The purpose of this is to uncover weaknesses in the initial plan and to optimize sequencing and delegation to increase the likelihood of achieving goals. Further, adaptive planning can be supported in \textit{during-incident reviews} by updating the current status, upon which ASP will then compute new alternatives. % and corresponding goal achievement measures. At this point, initial goals may no longer be viable and the explicit suggestion of prior sub-optimal goals now worth pursuing can be a game-changer under stress. The conceptual basis we lay out in terms of delegation and sequencing can be readily extended with further planning factors, such as resource requirements, role transfer and goal achievement.
Address Norwegian Computing Center; Norwegian Computing Center
Corporate Author Thesis
Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 978-1-949373-61-5 ISBN Medium
Track AI and Intelligent Systems for Crises and Risks Expedition Conference 18th International Conference on Information Systems for Crisis Response and Management
Notes audun.stolpe@its.uio.no Approved no
Call Number ISCRAM @ idladmin @ Serial 2310
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