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Unifying planning and scheduling as timelines in a component-based perspective
Örebro University, School of Science and Technology. (Center for Applied Autonomous Sensor Systems)ORCID iD: 0000-0002-9652-7864
2008 (English)In: Archives of Control Science, ISSN 1230-2384, Vol. 18, no 2, 231-271 p.Article in journal (Refereed) Published
Abstract [en]

The timeline-based approach to planning represents an effective alternative to classical planning for complex domains requiring the use of both temporal reasoning and scheduling features. This paper discusses the constraint-based approach to timeline planning and scheduling introduced in OMPS.  OMPS is a an architecture for problem solving which draws inspiration from both control theory and constraint-based reasoning, and which is based on the notion of components.The rationale behind the component-based approach shares with classical control theory a basic modeling perspective: the planning and scheduling problem is represented by identifying a set of relevant domain components which need to be controlled to obtain a desired temporal behavior for the entire system. Components are entities whose properties may vary in time and which model one or more physical (or logical) domain subsystems relevant to a given planning context. The planner/scheduler plays the role of the controller for these entities, and reasons in terms of constraints that bound their internal evolutions and the desired properties of the generated behaviors (goals). Our work complements this modeling assumption with a constraint-based computational framework.  Admissible temporal behaviors of components are specified as a set of causal constraints within a rich temporal specification, and goals are specified as temporal constraint preferences.  The OMPS software architecture presented in this paper combines both specific and generic constraint solvers in defining consistent timelines which satisfy a given set of goals.

Place, publisher, year, edition, pages
Versita , 2008. Vol. 18, no 2, 231-271 p.
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-24033OAI: oai:DiVA.org:oru-24033DiVA: diva2:540638
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APSI
Available from: 2013-03-18 Created: 2012-07-10 Last updated: 2018-01-12Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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