AI SearchAction representation languages and planning with incomplete information for UNIX programming
Call Number: AIT Thesis no. CS-01-15 Material type:
SeriesSeries: Asian Institute of Technology. Thesis ; no. CS-01-15Publication details: Bangkok : Asian Institute of Technology, 2001Description: 76 pSubject(s): Online resources: Dissertation note: Thesis (M.Sc.) - Asian Institute of Technology, 2001 Summary: This thesis deals with planning problems in the UNIX domain. It studies the UNIX environment, and represents the UNIX domains in the first order logic. The thesis also represents UNIX commands as actions in an action representation language. Those actions are then used in planners to solve problems in the UNIX system automatically. The thesis also builds a partial order planner, which uses the proposed actions to satisfy user requests. The built planner is not only able to handle universal quantification, conditional effect, but also to capture an agent's incomplete information about the world by extending the classical planner to handle information goals, as well as generate an executing plan in the presence of incomplete information by interleaving planning and execution.
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Asian Institute of Technology Library AIT Publications | AIT Thesis no. CS-01-15 (Browse shelf(Opens below)) | 1 | Available | 30050120674949 | |||||||||||||
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Asian Institute of Technology Library Archives | AIT Thesis no. CS-01-15 (Browse shelf(Opens below)) | 3 | Available | 30050120914642 |
A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Advanced Technologies
Thesis (M.Sc.) - Asian Institute of Technology, 2001
This thesis deals with planning problems in the UNIX domain. It studies the UNIX environment, and represents the UNIX domains in the first order logic. The thesis also represents UNIX commands as actions in an action representation language. Those actions are then used in planners to solve problems in the UNIX system automatically. The thesis also builds a partial order planner, which uses the proposed actions to satisfy user requests. The built planner is not only able to handle universal quantification, conditional effect, but also to capture an agent's incomplete information about the world by extending the classical planner to handle information goals, as well as generate an executing plan in the presence of incomplete information by interleaving planning and execution.
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