{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/69299"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/69299","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Hierarchical Plan Formation and Failure Recovery in the Flight Domain","abstract":"Expert planners have always been confronted with the domain complexity problem. This problem surfaced with the early works in automatic problem solving and has been a formidable obstacle ever since. The flight domain places additional demands on the planner due to the domain's complex and dynamic nature. This research presents a planning architecture that can perform both planning and recovery planning in the flight domain.","abstract_html":"Expert planners have always been confronted with the domain complexity problem. This problem surfaced with the early works in automatic problem solving and has been a formidable obstacle ever since. The flight domain places additional demands on the planner due to the domain's complex and dynamic nature. This research presents a planning architecture that can perform both planning and recovery planning in the flight domain.","abstract_has_math":false,"creators":["Chen, David Chihping"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Electrical Engineering","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-12-15T19:04:51Z","date_published":"2014-12-15T19:04:51Z","updated_at":"2026-07-22T22:26:00Z","subjects":["Physics, Electricity and Magnetism"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(UMI)AAI8511594"],"render_values":[{"text":"(UMI)AAI8511594","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/69299","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Chen, David Chihping"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-12-15T19:04:51Z","10000-01-01","1985"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Physics, Electricity and Magnetism"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/69299","(UMI)AAI8511594"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Expert planners have always been confronted with the domain complexity problem. This problem surfaced with the early works in automatic problem solving and has been a formidable obstacle ever since. The flight domain places additional demands on the planner due to the domain's complex and dynamic nature. This research presents a planning architecture that can perform both planning and recovery planning in the flight domain.","The key to a robust planner that can function in a complex and dynamic domain is the vertical decomposition of the domain knowledge. The decomposition is semantic in nature where the flight domain is decomposed into four minidomains. Each minidomain models the flight domain along some degree of global viewpoint, hence, the vertical hierarchy of semantic levels. The decomposition of the flight domain into four nearly independent minidomains reduces the domain complexity confronted by the planner. The explicit modeling of the different degrees of global viewpoint further reduces the domain complexity geometrically. The vertical decomposition of the domain knowledge results in shallow planning and shallow recovery planning.","Made available in DSpace on 2014-12-15T19:04:51Z (GMT). No. of bitstreams: 1 8511594.pdf: 5570225 bytes, checksum: b45177397b6b7177e3005ea3ee31ab52 (MD5) Previous issue date: 1985","Embargo set by: Seth Robbins for item 69465 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","221 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985."]},{"key":"dc:title","label":"Title","values":["Hierarchical Plan Formation and Failure Recovery in the Flight Domain"]}]}],"canonical_facts":{"dc:creator":["Chen, David Chihping"],"dc:date":["2014-12-15T19:04:51Z","10000-01-01","1985"],"dc:description":["Expert planners have always been confronted with the domain complexity problem. This problem surfaced with the early works in automatic problem solving and has been a formidable obstacle ever since. The flight domain places additional demands on the planner due to the domain's complex and dynamic nature. This research presents a planning architecture that can perform both planning and recovery planning in the flight domain.","The key to a robust planner that can function in a complex and dynamic domain is the vertical decomposition of the domain knowledge. The decomposition is semantic in nature where the flight domain is decomposed into four minidomains. Each minidomain models the flight domain along some degree of global viewpoint, hence, the vertical hierarchy of semantic levels. The decomposition of the flight domain into four nearly independent minidomains reduces the domain complexity confronted by the planner. The explicit modeling of the different degrees of global viewpoint further reduces the domain complexity geometrically. The vertical decomposition of the domain knowledge results in shallow planning and shallow recovery planning.","Made available in DSpace on 2014-12-15T19:04:51Z (GMT). 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