{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/19612"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/19612","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Goal-directed qualitative reasoning with partial states","abstract":"This research explores the representational and computational complexities of qualitative reasoning about time-varying behavior. Traditional techniques employ qualitative simulation (QS) to compute envisionments (i.e. state-transition graphs) representing all possible behaviors. Unfortunately, QS exhaustively case-splits on all choices, regardless of specific task goals. It reasons with completely described states and explores every (ambiguous) future of each.","abstract_html":"This research explores the representational and computational complexities of qualitative reasoning about time-varying behavior. Traditional techniques employ qualitative simulation (QS) to compute envisionments (i.e. state-transition graphs) representing all possible behaviors. Unfortunately, QS exhaustively case-splits on all choices, regardless of specific task goals. It reasons with completely described states and explores every (ambiguous) future of each.","abstract_has_math":false,"creators":["Decoste, Dennis Martin"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Winseus, Marianne"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-05-07T12:13:01Z","date_published":"2011-05-07T12:13:01Z","updated_at":"2026-07-22T22:25:14Z","subjects":["Computer Science"],"languages":["eng"],"rights":["Copyright 1994 Decoste, Dennis Martin"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9503174","(UMI)AAI9503174"],"render_values":[{"text":"AAI9503174","href":null,"code":true},{"text":"(UMI)AAI9503174","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/19612","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Winseus, Marianne"]},{"key":"dc:creator","label":"Author","values":["Decoste, Dennis Martin"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2011-05-07T12:13:01Z","10000-01-01","1994"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"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":["Computer Science"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 1994 Decoste, Dennis Martin"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9503174","(UMI)AAI9503174","http://hdl.handle.net/2142/19612"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This research explores the representational and computational complexities of qualitative reasoning about time-varying behavior. Traditional techniques employ qualitative simulation (QS) to compute envisionments (i.e. state-transition graphs) representing all possible behaviors. Unfortunately, QS exhaustively case-splits on all choices, regardless of specific task goals. It reasons with completely described states and explores every (ambiguous) future of each.","In this thesis we introduce a new representation, called sufficient discriminatory envisionments (SUDE's), which addresses these problems. SUDE's discriminate the possible behavior space by whether the goal is possible, impossible, or inevitable from each state in that space. Our techniques for generating SUDE's strive to reason with the smallest state descriptions which are sufficient for making these discriminations.","We present algorithms for generating SUDE's via a two-stage process. First, exhaustive regression sketches the space of possible paths between the initial and goal states. Second, we qualify these possible paths, identifying conditions under which the goal is impossible or inevitable and finding all possible transitions between these paths.","We formulate Nature's regression operators in terms of minimal chunks of causality, exploiting the causal, compositional nature of Qualitative Process Theory models. We integrate continuity-based and minimality-based theories of change to support discontinuous change due to actions and modelling simplifications.","We discuss our implementation of these techniques and our test examples in three domains, which we call ball-world, tank-world, and kitchen-world.","Made available in DSpace on 2011-05-07T12:13:01Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9503174.pdf: 6981264 bytes, checksum: ba8cc68459fa1cfdeb31368114eccb16 (MD5) Previous issue date: 1994","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:38:13Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:15:53-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission","ETDs are only available to UIUC Users without author permission","U of I Only"]},{"key":"dc:title","label":"Title","values":["Goal-directed qualitative reasoning with partial states"]}]}],"canonical_facts":{"dc:contributor":["Winseus, Marianne"],"dc:creator":["Decoste, Dennis Martin"],"dc:date":["2011-05-07T12:13:01Z","10000-01-01","1994"],"dc:description":["This research explores the representational and computational complexities of qualitative reasoning about time-varying behavior. Traditional techniques employ qualitative simulation (QS) to compute envisionments (i.e. state-transition graphs) representing all possible behaviors. Unfortunately, QS exhaustively case-splits on all choices, regardless of specific task goals. It reasons with completely described states and explores every (ambiguous) future of each.","In this thesis we introduce a new representation, called sufficient discriminatory envisionments (SUDE's), which addresses these problems. SUDE's discriminate the possible behavior space by whether the goal is possible, impossible, or inevitable from each state in that space. Our techniques for generating SUDE's strive to reason with the smallest state descriptions which are sufficient for making these discriminations.","We present algorithms for generating SUDE's via a two-stage process. First, exhaustive regression sketches the space of possible paths between the initial and goal states. Second, we qualify these possible paths, identifying conditions under which the goal is impossible or inevitable and finding all possible transitions between these paths.","We formulate Nature's regression operators in terms of minimal chunks of causality, exploiting the causal, compositional nature of Qualitative Process Theory models. We integrate continuity-based and minimality-based theories of change to support discontinuous change due to actions and modelling simplifications.","We discuss our implementation of these techniques and our test examples in three domains, which we call ball-world, tank-world, and kitchen-world.","Made available in DSpace on 2011-05-07T12:13:01Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9503174.pdf: 6981264 bytes, checksum: ba8cc68459fa1cfdeb31368114eccb16 (MD5) Previous issue date: 1994","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:38:13Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:15:53-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission","ETDs are only available to UIUC Users without author permission","U of I Only"],"dc:identifier":["AAI9503174","(UMI)AAI9503174","http://hdl.handle.net/2142/19612"],"dc:language":["eng"],"dc:rights":["Copyright 1994 Decoste, Dennis Martin"],"dc:subject":["Computer Science"],"dc:title":["Goal-directed qualitative reasoning with partial states"],"dc:type":["text"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:14Z"}