Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1957/6170
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dc.contributorFern, Alan-
dc.contributorTadepalli, Prasad-
dc.contributorWong, Weng-Keen-
dc.contributorPavol, Mike-
dc.date2007-07-24T16:27:47Z-
dc.date2007-07-24T16:27:47Z-
dc.date2007-06-15-
dc.date2007-07-24T16:27:47Z-
dc.date.accessioned2013-10-16T07:55:02Z-
dc.date.available2013-10-16T07:55:02Z-
dc.date.issued2013-10-16-
dc.identifierhttp://hdl.handle.net/1957/6170-
dc.identifier.urihttp://koha.mediu.edu.my:8181/xmlui/handle/1957/6170-
dc.descriptionGraduation date: 2008-
dc.descriptionDomain-independent automated planning is concerned with computing a sequence of actions that can transform an initial state into a desired goal state. Resource production domains form an interesting class of such problems, in that they typically require reasoning about concurrent durative-actions with continuous effects while minimizing some cost function. Although formulating planning problems as instances of SAT has proven to be very successful within the realm of STRIPS planning problems, where states and time are discrete and actions are instantaneous, it is unclear whether the same success can be transferred to resource production. Some of the major drawbacks to these systems are that they do not support reasoning about metric quantities, continuous time, and cost functions. TM-LPSAT was one of the first successful systems to reason about both metric quantities and continuous time within a SAT framework. However, TM-LPSAT does not provide a way to reason about cost functions. In this thesis, we extend the framework in a way that allows it to be capable of minimizing the costs, in our case makespans, of the plans that it finds.-
dc.languageen_US-
dc.subjectAI-
dc.subjectSAT-
dc.subjectPlanning-
dc.subjectResource Production-
dc.titleA SAT-based planning framework for optimizing resource production-
dc.typeThesis-
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