[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"_public_publisher_byId_76b2b6fe-3829-47b1-b77e-58b2d7093279":3,"_public_publication_all{\"sortAscending\":false,\"sortField\":\"updateTime\",\"page\":0,\"size\":10,\"facet\":true,\"searchKey\":\"publisherId:76b2b6fe-3829-47b1-b77e-58b2d7093279,\"}":76},{"code":4,"data":5,"meta":18},"SUCCESS",{"id":6,"createTime":7,"updateTime":8,"relativeEntities":9,"slug":10,"properties":11,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":20,"manageAffiliations":32,"indexDatabases":40,"url":18,"thumbnailPath":18,"statistic":18,"gsStatistic":18,"type":18,"analyzePriority":18},"76b2b6fe-3829-47b1-b77e-58b2d7093279","2023-12-05T05:59:49.185+00:00","2025-11-21T10:03:39.531+00:00",[],"Artificial-Intelligence",{"issn":12,"title":14},{"VOID":13},"00043702",{"EN":15},"Artificial Intelligence","PUBLISHER","PENDING",null,0,[21,26],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":23,"label":24,"description":25,"parentId":18,"standard":18,"scholarHubFieldId":18},"6a3cb349-a9fc-40fb-9aa8-c9946de1e629",[],{"EN":15},{},{"id":27,"createTime":18,"updateTime":18,"relativeEntities":28,"label":29,"description":31,"parentId":18,"standard":18,"scholarHubFieldId":18},"64d33793-c08c-4249-87eb-4cddd659189b",[],{"EN":30},"Linguistics and Language",{},[33],{"id":34,"createTime":18,"updateTime":18,"relativeEntities":35,"slug":18,"properties":36,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":39,"statistic":18},"c749757b-dddf-4e6f-9697-b9c441adc06c",[],{"title":37},{"EN":38},"Elsevier",[],[41,58],{"id":42,"indexDatabase":43,"url":55,"indexYears":18,"academicFieldIds":56,"indexDatabaseRanking":18},"dfcd1cb8-0241-460f-86fd-f9daf6e6460b",{"id":44,"createTime":18,"updateTime":18,"relativeEntities":45,"label":46,"description":48,"key":51,"publicationTags":52,"standard":18},"a4921856-b128-4d9f-8f1f-e80813d3bbd4",[],{"EN":47,"VI":47},"ISI\u002FSCIE - Science Citation Index Expanded",{"EN":49,"VI":50},"SCIE database","Cơ sở dữ liệu SCIE","scie",[53,54],"SCIE","ISI","https:\u002F\u002Fmjl.clarivate.com\u002Fsearch-results?issn=0004-3702",[57],"1acb72da-cafe-4349-b117-01c5aabcd399",{"id":59,"indexDatabase":60,"url":70,"indexYears":71,"academicFieldIds":72,"indexDatabaseRanking":75},"1efcff22-24db-43dd-afbd-d7c1fad3bca2",{"id":61,"createTime":18,"updateTime":18,"relativeEntities":62,"label":63,"description":65,"key":67,"publicationTags":68,"standard":18},"3c7051d4-eb7d-4c57-a56b-36fc74c5d1e9",[],{"EN":64,"VI":64},"Scopus - Elsevier",{"EN":64,"VI":66},"Cơ sở dữ liệu Scopus thuộc Elsevier","scopus",[69],"SCOPUS","https:\u002F\u002Fwww.scopus.com\u002Fsourceid\u002F23675","1968,1970-2025",[73,74],"ea95f5ee-62c8-4ccb-8e3e-d3a8bc9e97cb","f2c28a7b-0a02-471f-b7e1-c5b1d4ab375d","SCOPUS__Q1",{"meta":77,"data":79},{"total":78},"1616",[80,201,334,412,642,741,835,954,1081,1176],{"id":81,"createTime":82,"updateTime":83,"relativeEntities":84,"slug":85,"properties":86,"entityType":96,"verifyStatus":97,"verifyTime":98,"verifyNote":99,"languages":18,"translateLanguages":100,"viewCount":19,"primaryUrl":102,"fullTextUrl":18,"authors":103,"publicationType":122,"publisherRelationship":123,"citationCount":164,"citationInfo":165,"publishDate":196,"publishYear":166,"citationAnalyzeStatus":197,"lastCitationAnalyze":198,"indexDatabases":199,"openAccess":18,"references":18,"isForceReanalyzing":200},"a9b14b67-be66-407d-815f-c91e118133de","2023-12-05T08:57:36.667+00:00","2026-09-12T09:11:39.227+00:00",[],"Understanding-computers-and-cognition-A-new-foundation-for-design",{"title":87,"gsPaper":90,"references":92,"doi":94},{"EN":88,"VI":89},"Understanding computers and cognition: A new foundation for design","Hiểu về máy tính và nhận thức: Một nền tảng mới cho thiết kế",{"VOID":91},"[\"18130947294277928975\",\"9088851922584209569\"]",{"VOID":93},"Atkinson, 1979\nGarfinkel, 1967\nHeritage, 1984\nLynch, 1985\nSuchman, 1987\nZimmerman, 1971, The practicalities of rule use",{"VOID":95},"10.1016\u002F0004-3702(87)90024-5","PUBLICATION","VERIFIED","2024-06-26T05:52:05.787+00:00","Auto Verify",[101],"VI","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002F0004370287900245",[104],{"id":105,"sortIndex":19,"researcher":18,"roles":106,"affiliations":108,"properties":117,"displayName":119,"givenName":18,"familyName":18},"f70a42d6-8387-4168-9e0c-d454a5f9ffb7",[107],"AUTHOR",[109],{"id":110,"sortIndex":19,"affiliation":111,"properties":18},"555626ad-bb88-4d74-93cf-cf8e66f4c0f8",{"id":110,"createTime":18,"updateTime":18,"relativeEntities":112,"slug":18,"properties":113,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":116,"statistic":18},[],{"title":114},{"VI":115},"Xerox Palo Alto Research Center Palo Alto, CA 94304, U.S.A.",[],{"title":118,"gsAuthor":120},{"VI":119},"Lucy A. Suchman",{"VOID":121},"[\"ASV8erkAAAAJ\"]","ARTICLE",{"url":102,"publisher":124,"properties":159},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":125,"slug":10,"properties":126,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":129,"manageAffiliations":138,"indexDatabases":144,"url":18,"thumbnailPath":18,"statistic":18,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"issn":127,"title":128},{"VOID":13},{"EN":15},[130,134],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":131,"label":132,"description":133,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":15},{},{"id":27,"createTime":18,"updateTime":18,"relativeEntities":135,"label":136,"description":137,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":30},{},[139],{"id":34,"createTime":18,"updateTime":18,"relativeEntities":140,"slug":18,"properties":141,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":143,"statistic":18},[],{"title":142},{"EN":38},[],[145,152],{"id":42,"indexDatabase":146,"url":55,"indexYears":18,"academicFieldIds":151,"indexDatabaseRanking":18},{"id":44,"createTime":18,"updateTime":18,"relativeEntities":147,"label":148,"description":149,"key":51,"publicationTags":150,"standard":18},[],{"EN":47,"VI":47},{"EN":49,"VI":50},[53,54],[57],{"id":59,"indexDatabase":153,"url":70,"indexYears":71,"academicFieldIds":158,"indexDatabaseRanking":75},{"id":61,"createTime":18,"updateTime":18,"relativeEntities":154,"label":155,"description":156,"key":67,"publicationTags":157,"standard":18},[],{"EN":64,"VI":64},{"EN":64,"VI":66},[69],[73,74],{"pages":160,"volume":162},{"VOID":161},"227-232",{"VOID":163},"31",11209,{"total":164,"publishYear":166,"statisticByYear":167},1987,{"1987":168,"1988":169,"1989":170,"1990":171,"1991":172,"1992":173,"1993":174,"1994":174,"1995":175,"1996":176,"1997":177,"1998":172,"1999":178,"2000":179,"2001":180,"2002":169,"2003":181,"2004":182,"2005":183,"2006":184,"2007":185,"2008":181,"2009":175,"2010":186,"2011":187,"2012":181,"2013":188,"2014":170,"2015":189,"2016":181,"2017":190,"2018":191,"2019":192,"2020":193,"2021":189,"2022":188,"2023":188,"2024":171,"2025":194,"2026":195},2,10,30,37,35,23,34,59,62,28,67,79,57,48,45,86,76,75,80,64,33,14,38,44,47,51,20,123,"1987-02-01","DONE_ANALYZE_CITATION","2026-07-20T19:06:56.780+00:00",[53,75],false,{"id":202,"createTime":203,"updateTime":204,"relativeEntities":205,"slug":206,"properties":207,"entityType":96,"verifyStatus":97,"verifyTime":216,"verifyNote":99,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":217,"fullTextUrl":18,"authors":218,"publicationType":122,"publisherRelationship":287,"citationCount":19,"citationInfo":328,"publishDate":331,"publishYear":329,"citationAnalyzeStatus":197,"lastCitationAnalyze":332,"indexDatabases":333,"openAccess":18,"references":18,"isForceReanalyzing":200},"13da08de-0861-4959-8113-8f2159a5de8d","2024-01-10T04:56:38.840+00:00","2026-07-24T08:30:00.444+00:00",[],"Variable-symmetry-breaking-in-numerical-constraint-problems",{"title":208,"gsPaper":210,"references":212,"doi":214},{"EN":209},"Variable symmetry breaking in numerical constraint problems",{"VOID":211},"[\"18432445909056879259\"]",{"VOID":213},"Goldsztejn, 2011, Symmetry breaking in numeric constraint problems, vol. 6876, 317\nVu, 2009, Interval propagation and search on directed acyclic graphs for numerical constraint solving, J. Glob. Optim., 45, 499, 10.1007\u002Fs10898-008-9386-7\nMerlet, 2009, Interval analysis for certified numerical solution of problems in robotics, Appl. Math. Comput. Sci., 19, 399\nGoldsztejn, 2008, Capabilities of constraint programming in safe global optimization, 601\nGent, 2006, Symmetry in constraint programming, 329\nWalsh, 2008, Breaking value symmetry, 1585\nWalsh, 2010, Parameterized complexity results in symmetry breaking, vol. 6478, 4\nMeseguer, 2001, Exploiting symmetries within constraint satisfaction search, Artif. Intell., 129, 133, 10.1016\u002FS0004-3702(01)00104-7\nGent, 2002, Groups and constraints: symmetry breaking during search, vol. 2470, 415\nFlener, 2002, Breaking row and column symmetries in matrix models, 462\nPuget, 2005, Symmetry breaking revisited, Constraints, 10, 23, 10.1007\u002Fs10601-004-5306-8\nRuiz de Angulo, 2009, Exploiting single-cycle symmetries in continuous constraint problems, J. Artif. Intell. Res., 34, 499, 10.1613\u002Fjair.2711\nLiberti, 2012, Reformulations in mathematical programming: automatic symmetry detection and exploitation, Math. Program., 131, 273, 10.1007\u002Fs10107-010-0351-0\nLiberti, 2014, Stabilizer-based symmetry breaking constraints for mathematical programs, J. Glob. Optim., 60, 183, 10.1007\u002Fs10898-013-0106-6\nGasca, 2005, Improving the computational efficiency in symmetrical numeric constraint satisfaction problems, 269\nJi, 2009, Solving global unconstrained optimization problems by symmetry-breaking, 107\nCosta, 2010, Formulation symmetries in circle packing, Electron. Notes Discrete Math., 36, 1303, 10.1016\u002Fj.endm.2010.05.165\nCrawford, 1996, Symmetry-breaking predicates for search problems, 148\nCohen, 2006, Symmetry definitions for constraint satisfaction problems, Constraints, 11, 115, 10.1007\u002Fs10601-006-8059-8\nNarodytska, 2013, Breaking symmetry with different orderings, vol. 8124, 545\nFrisch, 2006, Propagation algorithms for lexicographic ordering constraints, Artif. Intell., 170, 803, 10.1016\u002Fj.artint.2006.03.002\nJefferson, 2011, Automatic generation of constraints for partial symmetry breaking, vol. 6876, 729\nAho, 1972, The transitive reduction of a directed graph, SIAM J. Comput., 1, 131, 10.1137\u002F0201008\nPuget, 2005, Breaking symmetries in all different problems, 272\nSims, 1970, Computational methods in the study of permutation groups, 169\nMcKay, 2014, Practical graph isomorphism, II, J. Symb. Comput., 60, 94, 10.1016\u002Fj.jsc.2013.09.003\nFriedman, 2007, Fundamental domains for integer programs with symmetries, vol. 4616, 146\nDiaz y Diaz, 2014, Signed fundamental domains for totally real number fields, Proc. Lond. Math. Soc., 108, 965, 10.1112\u002Fplms\u002Fpdt025\nFrisch, 2006, Propagation algorithms for lexicographic ordering constraints, Artif. Intell., 170, 803, 10.1016\u002Fj.artint.2006.03.002\nElgabou, 2014, Encoding the lexicographic ordering constraint in sat modulo theories, 85\nGranvilliers, 2006, Algorithm 852: Realpaver: an interval solver using constraint satisfaction techniques, ACM Trans. Math. Softw., 32, 138, 10.1145\u002F1132973.1132980\nGoldsztejn, 2013, Constraint based computation of periodic orbits of chaotic dynamical systems, vol. 8124, 774\nMargot, 2010, Symmetry in integer linear programming, 647",{"VOID":215},"10.1016\u002Fj.artint.2015.08.006","2024-06-24T05:26:41.580+00:00","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0004370215001216",[219,236,254,271],{"id":220,"sortIndex":19,"researcher":18,"roles":221,"affiliations":222,"properties":231,"displayName":233,"givenName":18,"familyName":18},"0905c9f5-ddd8-4510-844c-d6d33a2ed549",[107],[223],{"id":224,"sortIndex":19,"affiliation":225,"properties":18},"a4b99746-27be-4b21-8e11-2628b0687c4e",{"id":224,"createTime":18,"updateTime":18,"relativeEntities":226,"slug":18,"properties":227,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":230,"statistic":18},[],{"title":228},{"VI":229},"IRCCyN\u002FCNRS, Nantes, France",[],{"title":232,"gsAuthor":234},{"VI":233},"Alexandre Goldsztejn",{"VOID":235},"[\"knvZjVwAAAAJ\"]",{"id":237,"sortIndex":238,"researcher":18,"roles":239,"affiliations":240,"properties":249,"displayName":251,"givenName":18,"familyName":18},"4a64838a-f47b-41e7-b203-6c74b9b3c313",1,[107],[241],{"id":242,"sortIndex":19,"affiliation":243,"properties":18},"0667bfe9-7048-41f5-91cd-d3e920647e12",{"id":242,"createTime":18,"updateTime":18,"relativeEntities":244,"slug":18,"properties":245,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":248,"statistic":18},[],{"title":246},{"VI":247},"LINA, Université de Nantes\u002FCNRS, Nantes, France",[],{"title":250,"gsAuthor":252},{"VI":251},"Christophe Jermann",{"VOID":253},"[\"-wEIYj0AAAAJ\"]",{"id":255,"sortIndex":168,"researcher":18,"roles":256,"affiliations":257,"properties":266,"displayName":268,"givenName":18,"familyName":18},"81f6f003-73a7-43b1-94ac-24f68502418c",[107],[258],{"id":259,"sortIndex":19,"affiliation":260,"properties":18},"9dbc50b4-f6d4-4ee5-888c-404fdc94f99e",{"id":259,"createTime":18,"updateTime":18,"relativeEntities":261,"slug":18,"properties":262,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":265,"statistic":18},[],{"title":263},{"VI":264},"Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Barcelona, Spain",[],{"title":267,"gsAuthor":269},{"VI":268},"Vicente Ruiz de Angulo",{"VOID":270},"[\"m1eoR-cAAAAJ\"]",{"id":272,"sortIndex":273,"researcher":18,"roles":274,"affiliations":275,"properties":282,"displayName":284,"givenName":18,"familyName":18},"e5fd6e80-09e3-40b2-8422-e8cd384554ac",3,[107],[276],{"id":259,"sortIndex":19,"affiliation":277,"properties":18},{"id":259,"createTime":18,"updateTime":18,"relativeEntities":278,"slug":18,"properties":279,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":281,"statistic":18},[],{"title":280},{"VI":264},[],{"title":283,"gsAuthor":285},{"VI":284},"Carme Torras",{"VOID":286},"[\"zXsQ3CkAAAAJ\"]",{"url":217,"publisher":288,"properties":323},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":289,"slug":10,"properties":290,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":293,"manageAffiliations":302,"indexDatabases":308,"url":18,"thumbnailPath":18,"statistic":18,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"issn":291,"title":292},{"VOID":13},{"EN":15},[294,298],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":295,"label":296,"description":297,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":15},{},{"id":27,"createTime":18,"updateTime":18,"relativeEntities":299,"label":300,"description":301,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":30},{},[303],{"id":34,"createTime":18,"updateTime":18,"relativeEntities":304,"slug":18,"properties":305,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":307,"statistic":18},[],{"title":306},{"EN":38},[],[309,316],{"id":42,"indexDatabase":310,"url":55,"indexYears":18,"academicFieldIds":315,"indexDatabaseRanking":18},{"id":44,"createTime":18,"updateTime":18,"relativeEntities":311,"label":312,"description":313,"key":51,"publicationTags":314,"standard":18},[],{"EN":47,"VI":47},{"EN":49,"VI":50},[53,54],[57],{"id":59,"indexDatabase":317,"url":70,"indexYears":71,"academicFieldIds":322,"indexDatabaseRanking":75},{"id":61,"createTime":18,"updateTime":18,"relativeEntities":318,"label":319,"description":320,"key":67,"publicationTags":321,"standard":18},[],{"EN":64,"VI":64},{"EN":64,"VI":66},[69],[73,74],{"pages":324,"volume":326},{"VOID":325},"105-125",{"VOID":327},"229",{"total":19,"publishYear":329,"statisticByYear":330},2015,{},"2015-12-01","2026-07-24T08:30:00.443+00:00",[53,75],{"id":335,"createTime":336,"updateTime":337,"relativeEntities":338,"slug":339,"properties":340,"entityType":96,"verifyStatus":97,"verifyTime":347,"verifyNote":99,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":348,"fullTextUrl":18,"authors":349,"publicationType":122,"publisherRelationship":365,"citationCount":19,"citationInfo":406,"publishDate":409,"publishYear":407,"citationAnalyzeStatus":197,"lastCitationAnalyze":410,"indexDatabases":411,"openAccess":18,"references":18,"isForceReanalyzing":200},"a655c447-3017-4ea1-8015-6e48183944d4","2024-01-13T09:58:37.946+00:00","2026-07-24T01:52:23.608+00:00",[],"Artificial-intelligence-applications-for-business-management",{"title":341,"gsPaper":343,"doi":345},{"EN":342},"Artificial intelligence applications for business management",{"VOID":344},"[\"5801432133588763679\",\"13234843532694727146\"]",{"VOID":346},"10.1016\u002F0004-3702(86)90055-x","2024-04-29T00:43:04.545+00:00","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002F000437028690055X",[350],{"id":351,"sortIndex":19,"researcher":18,"roles":352,"affiliations":353,"properties":362,"displayName":364,"givenName":18,"familyName":18},"9fac96e2-624e-48a3-90a1-2ca967faa072",[107],[354],{"id":355,"sortIndex":19,"affiliation":356,"properties":18},"19962cde-a75b-4428-a4e3-a78fec45ba21",{"id":355,"createTime":18,"updateTime":18,"relativeEntities":357,"slug":18,"properties":358,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":361,"statistic":18},[],{"title":359},{"VI":360},"Xerox Palo Alto Research Center, 3333 Coyote Hill Road, Palo Alto, CA 94305, U.S.A.",[],{"title":363},{"VI":364},"Mark Stefik",{"url":348,"publisher":366,"properties":401},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":367,"slug":10,"properties":368,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":371,"manageAffiliations":380,"indexDatabases":386,"url":18,"thumbnailPath":18,"statistic":18,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"issn":369,"title":370},{"VOID":13},{"EN":15},[372,376],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":373,"label":374,"description":375,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":15},{},{"id":27,"createTime":18,"updateTime":18,"relativeEntities":377,"label":378,"description":379,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":30},{},[381],{"id":34,"createTime":18,"updateTime":18,"relativeEntities":382,"slug":18,"properties":383,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":385,"statistic":18},[],{"title":384},{"EN":38},[],[387,394],{"id":42,"indexDatabase":388,"url":55,"indexYears":18,"academicFieldIds":393,"indexDatabaseRanking":18},{"id":44,"createTime":18,"updateTime":18,"relativeEntities":389,"label":390,"description":391,"key":51,"publicationTags":392,"standard":18},[],{"EN":47,"VI":47},{"EN":49,"VI":50},[53,54],[57],{"id":59,"indexDatabase":395,"url":70,"indexYears":71,"academicFieldIds":400,"indexDatabaseRanking":75},{"id":61,"createTime":18,"updateTime":18,"relativeEntities":396,"label":397,"description":398,"key":67,"publicationTags":399,"standard":18},[],{"EN":64,"VI":64},{"EN":64,"VI":66},[69],[73,74],{"pages":402,"volume":404},{"VOID":403},"345-348",{"VOID":405},"28",{"total":19,"publishYear":407,"statisticByYear":408},1986,{},"1986-05-01","2026-07-24T01:52:23.607+00:00",[53,75],{"id":413,"createTime":414,"updateTime":415,"relativeEntities":416,"slug":417,"properties":418,"entityType":96,"verifyStatus":97,"verifyTime":425,"verifyNote":99,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":426,"fullTextUrl":18,"authors":427,"publicationType":122,"publisherRelationship":488,"citationCount":19,"citationInfo":529,"publishDate":532,"publishYear":530,"citationAnalyzeStatus":17,"lastCitationAnalyze":533,"indexDatabases":534,"openAccess":18,"references":535,"isForceReanalyzing":200},"faac8fdf-732c-415a-800c-101bcc8b579b","2023-12-12T16:03:34.695+00:00","2026-07-22T21:51:53.145+00:00",[],"Adopt-asynchronous-distributed-constraint-optimization-with-quality-guarantees",{"title":419,"gsPaper":421,"doi":423},{"EN":420},"Adopt: asynchronous distributed constraint optimization with quality guarantees",{"VOID":422},"[\"16057265086940645842\"]",{"VOID":424},"10.1016\u002Fj.artint.2004.09.003","2024-04-29T12:33:42.055+00:00","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0004370204001511",[428,443,456,471],{"id":429,"sortIndex":19,"researcher":18,"roles":430,"affiliations":431,"properties":440,"displayName":442,"givenName":18,"familyName":18},"cc7a7f60-4579-41ac-b528-804830511897",[107],[432],{"id":433,"sortIndex":19,"affiliation":434,"properties":18},"6ac8e004-78b1-4cbb-905d-96add959aa77",{"id":433,"createTime":18,"updateTime":18,"relativeEntities":435,"slug":18,"properties":436,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":439,"statistic":18},[],{"title":437},{"VI":438},"Information Sciences Institute and Computer Science Department, University of Southern California, Marina del Rey, CA 90292, USA",[],{"title":441},{"VI":442},"Pragnesh Jay Modi",{"id":444,"sortIndex":238,"researcher":18,"roles":445,"affiliations":446,"properties":453,"displayName":455,"givenName":18,"familyName":18},"ed2a1219-e306-42c7-83e1-207490c38533",[107],[447],{"id":433,"sortIndex":19,"affiliation":448,"properties":18},{"id":433,"createTime":18,"updateTime":18,"relativeEntities":449,"slug":18,"properties":450,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":452,"statistic":18},[],{"title":451},{"VI":438},[],{"title":454},{"VI":455},"Wei-Min Shen",{"id":457,"sortIndex":168,"researcher":18,"roles":458,"affiliations":459,"properties":466,"displayName":468,"givenName":18,"familyName":18},"d5a6a87f-b0ec-4c8a-8e15-af5c952dd852",[107],[460],{"id":433,"sortIndex":19,"affiliation":461,"properties":18},{"id":433,"createTime":18,"updateTime":18,"relativeEntities":462,"slug":18,"properties":463,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":465,"statistic":18},[],{"title":464},{"VI":438},[],{"title":467,"gsAuthor":469},{"VI":468},"Milind Tambe",{"VOID":470},"[\"YOVZiJkAAAAJ\"]",{"id":472,"sortIndex":273,"researcher":18,"roles":473,"affiliations":474,"properties":483,"displayName":485,"givenName":18,"familyName":18},"3021bbc3-a2e5-4a00-b9b8-cce47f1fc3ad",[107],[475],{"id":476,"sortIndex":19,"affiliation":477,"properties":18},"a4aea966-0ba8-497b-a191-2efdbdfd828e",{"id":476,"createTime":18,"updateTime":18,"relativeEntities":478,"slug":18,"properties":479,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":482,"statistic":18},[],{"title":480},{"VI":481},"NTT Communication Science Labs, 2-4 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0237, Japan",[],{"title":484,"gsAuthor":486},{"VI":485},"Makoto Yokoo",{"VOID":487},"[\"dHXCX-sAAAAJ\"]",{"url":426,"publisher":489,"properties":524},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":490,"slug":10,"properties":491,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":494,"manageAffiliations":503,"indexDatabases":509,"url":18,"thumbnailPath":18,"statistic":18,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"issn":492,"title":493},{"VOID":13},{"EN":15},[495,499],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":496,"label":497,"description":498,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":15},{},{"id":27,"createTime":18,"updateTime":18,"relativeEntities":500,"label":501,"description":502,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":30},{},[504],{"id":34,"createTime":18,"updateTime":18,"relativeEntities":505,"slug":18,"properties":506,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":508,"statistic":18},[],{"title":507},{"EN":38},[],[510,517],{"id":42,"indexDatabase":511,"url":55,"indexYears":18,"academicFieldIds":516,"indexDatabaseRanking":18},{"id":44,"createTime":18,"updateTime":18,"relativeEntities":512,"label":513,"description":514,"key":51,"publicationTags":515,"standard":18},[],{"EN":47,"VI":47},{"EN":49,"VI":50},[53,54],[57],{"id":59,"indexDatabase":518,"url":70,"indexYears":71,"academicFieldIds":523,"indexDatabaseRanking":75},{"id":61,"createTime":18,"updateTime":18,"relativeEntities":519,"label":520,"description":521,"key":67,"publicationTags":522,"standard":18},[],{"EN":64,"VI":64},{"EN":64,"VI":66},[69],[73,74],{"pages":525,"volume":527},{"VOID":526},"149-180",{"VOID":528},"161",{"total":19,"publishYear":530,"statisticByYear":531},2005,{},"2005-01-01","2026-07-22T21:51:53.144+00:00",[53,75],[536,542,545,548,551,554,557,563,566,569,572,575,578,581,584,587,593,596,599,602,605,608,611,614,617,620,623,626,633,636,639],{"id":537,"text":538,"url":539,"identifiers":540},"4c68646b-0035-4279-8000-0006b275d4fa","Armstrong, 1997, Dynamic prioritization of complex agents in distributed constraint satisfaction problems, 620","https:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs10440-022-00541-7",{"doi":541},"10.1007\u002Fs10440-022-00541-7",{"id":18,"text":543,"url":18,"identifiers":544},"Barrett, 1999, Autonomy architectures for a constellation of spacecraft",{},{"id":18,"text":546,"url":18,"identifiers":547},"Bistarelli, 1995, Constraint solving over semirings, 624",{},{"id":537,"text":549,"url":539,"identifiers":550},"Caulder, 1993, Modsaf behavior simulation and control",{"doi":541},{"id":18,"text":552,"url":18,"identifiers":553},"Chalupsky, 2001, Electric elves: Applying agent technology to support human organizations, 51",{},{"id":537,"text":555,"url":539,"identifiers":556},"Collin, 1991, On the feasibility of distributed constraint satisfaction, 318",{"doi":541},{"id":558,"text":559,"url":560,"identifiers":561},"3500f885-3c0e-4473-8452-917108c171a4","Collin, 1994, Self-stabilizing depth first search, Inform. Process. Lett., 49, 297, 10.1016\u002F0020-0190(94)90103-1","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002F0020019094901031",{"doi":562},"10.1016\u002F0020-0190(94)90103-1",{"id":18,"text":564,"url":18,"identifiers":565},"Dechter, 1990, Optimization in constraint networks",{},{"id":537,"text":567,"url":539,"identifiers":568},"Fitzpatrick, 2001, An experimental assessment of a stochastic, anytime, decentralized, soft colourer for sparse graphs",{"doi":541},{"id":18,"text":570,"url":18,"identifiers":571},"Frei, 1999, Resource allocation in networks using abstraction and constraint satisfaction techniques, 204",{},{"id":537,"text":573,"url":539,"identifiers":574},"Freuder, 1985, Taking advantage of stable sets of variables in constraint satisfaction problems, 1076",{"doi":541},{"id":18,"text":576,"url":18,"identifiers":577},"Hamadi, 1998, Distributed intelligent backtracking, 219",{},{"id":537,"text":579,"url":539,"identifiers":580},"Hirayama, 1997, Distributed partial constraint satisfaction problem, 222",{"doi":541},{"id":537,"text":582,"url":539,"identifiers":583},"Hirayama, 2000, An approach to over-constrained distributed constraint satisfaction problems: Distributed hierarchical constraint satisfaction",{"doi":541},{"id":18,"text":585,"url":18,"identifiers":586},"Kitano, 1999",{},{"id":18,"text":588,"url":589,"identifiers":590},"Korf, 1985, Depth-first iterative-deepening: an optimal admissible tree search, Artificial Intelligence, 27, 97, 10.1016\u002F0004-3702(85)90084-0","https:\u002F\u002Fdoi.org\u002F10.1016\u002F0004-3702(86)90035-4",{"openalex":591,"doi":592},"W4248795023","10.1016\u002F0004-3702(86)90035-4",{"id":537,"text":594,"url":539,"identifiers":595},"Lemaitre, 1997, An incomplete method for solving distributed valued constraint satisfaction problems",{"doi":541},{"id":537,"text":597,"url":539,"identifiers":598},"Liu, 1995, Exploiting problem structure for distributed constraint optimization",{"doi":541},{"id":18,"text":600,"url":18,"identifiers":601},"Lynch, 1996",{},{"id":537,"text":603,"url":539,"identifiers":604},"Meseguer, 2000, Distributed forward checking",{"doi":541},{"id":537,"text":606,"url":539,"identifiers":607},"Modi, 2003, An asynchronous complete method for distributed constraint optimization",{"doi":541},{"id":18,"text":609,"url":18,"identifiers":610},"Modi, 2003, Distributed constraint reasoning under unreliable communication",{},{"id":537,"text":612,"url":539,"identifiers":613},"P.J. Modi, Distributed constraint optimization for multiagent systems, PhD Thesis, University of Southern California, Marina del Rey, CA, 2003",{"doi":541},{"id":537,"text":615,"url":539,"identifiers":616},"Parunak, 1997, Distributed component-centered design as agent-based distributed constraint optimization",{"doi":541},{"id":537,"text":618,"url":539,"identifiers":619},"Schiex, 1995, Valued constraint satisfaction problems: Hard and easy problems, Montreal, Quebec, 631",{"doi":541},{"id":537,"text":621,"url":539,"identifiers":622},"Shen, 2002, Self-reconfigurable robots, IEEE Trans. Mechatron., 7",{"doi":541},{"id":18,"text":624,"url":18,"identifiers":625},"Silaghi, 2000, Asynchronous search with aggregations, 917",{},{"id":18,"text":627,"url":628,"identifiers":629},"Tambe, 1997, Towards flexible teamwork, J. Artificial Intelligence Res., 7, 83, 10.1613\u002Fjair.433","https:\u002F\u002Fdoi.org\u002F10.1613\u002Fjair.433",{"mag":630,"openalex":631,"doi":632},"1657704689","W1657704689","10.1613\u002Fjair.433",{"id":18,"text":634,"url":18,"identifiers":635},"Yokoo, 2001",{},{"id":537,"text":637,"url":539,"identifiers":638},"Yokoo, 1998, Distributed constraint satisfaction algorithm for complex local problems",{"doi":541},{"id":18,"text":640,"url":18,"identifiers":641},"Zhang, 2002, Distributed breakout revisited, 352",{},{"id":643,"createTime":644,"updateTime":645,"relativeEntities":646,"slug":647,"properties":648,"entityType":96,"verifyStatus":97,"verifyTime":657,"verifyNote":99,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":658,"fullTextUrl":18,"authors":659,"publicationType":122,"publisherRelationship":694,"citationCount":19,"citationInfo":735,"publishDate":738,"publishYear":736,"citationAnalyzeStatus":17,"lastCitationAnalyze":739,"indexDatabases":740,"openAccess":18,"references":18,"isForceReanalyzing":200},"0164b801-dcb8-4216-80ee-541484cbebc3","2024-01-17T20:46:25.910+00:00","2026-07-22T16:31:13.275+00:00",[],"Popularity-similarity-random-SAT-formulas",{"title":649,"gsPaper":651,"references":653,"doi":655},{"EN":650},"Popularity-similarity random SAT formulas",{"VOID":652},"[\"16190226018665484294\"]",{"VOID":654},"Achlioptas, 2000, Generating satisfiable problem instances, 256\nAnsótegui, 2009, On the structure of industrial SAT instances, 127\nAnsótegui, 2012, The community structure of SAT formulas, 410\nAnsótegui, 2014, The fractal dimension of SAT formulas, 107\nAnsótegui, 2015, Using community structure to detect relevant learnt clauses, 238\nAnsótegui, 2017, Structure features for SAT instances classification, J. Appl. Log., 23, 27, 10.1016\u002Fj.jal.2016.11.004\nAnsótegui, 2019, Community structure in industrial SAT instances, J. Artif. Intell. Res., 66, 443, 10.1613\u002Fjair.1.11741\nAnsótegui, 2009, Towards industrial-like random SAT instances, 387\nAnsótegui\nAudemard, 2009, Predicting learnt clauses quality in modern SAT solvers, 399\nBarabási, 1999, Emergence of scaling in random networks, Science, 286, 509, 10.1126\u002Fscience.286.5439.509\nBaud-Berthier, 2017, On the community structure of bounded model checking SAT problems, 65\nBiere, 2017, CaDiCaL, lingeling, plingeling, treengeling, YalSAT entering the SAT competition 2017, 14\nBiere, 2019, CaDiCaL at the SAT Race 2019, 8\nBoguñá, 2010, Sustaining the Internet with hyperbolic mapping, Nat. Commun., 1\nBringmann, 2019, Geometric inhomogeneous random graphs, Theor. Comput. Sci., 760, 35, 10.1016\u002Fj.tcs.2018.08.014\nCooper, 2007, Random 2-SAT with prescribed literal degrees, Algorithmica, 48, 249, 10.1007\u002Fs00453-007-0082-7\nDechter, 2003\nEén, 2003, An extensible SAT-solver, 502\nFreeman, 1995\nFriedrich, 2018, Sharpness of the satisfiability threshold for non-uniform random k-SAT, 273\nFriedrich, 2019, The satisfiability threshold for non-uniform random 2-SAT\nFriedrich, 2017, Bounds on the satisfiability threshold for power law distributed random SAT, vol. 87\nFriedrich, 2017, Phase transition for scale-free SAT formulas\nGent, 1999, Morphing: combining structure and randomness, 654\nGiráldez-Cru, 2015, A modularity-based random SAT instances generator, 1952\nGiráldez-Cru, 2016, Generating SAT instances with community structure, Artif. Intell., 238, 119, 10.1016\u002Fj.artint.2016.06.001\nGiráldez-Cru, 2017, Locality in random SAT instances, 638\nGomes, 1997, Problem structure in the presence of perturbations, 221\nHeule, 2004, March_eq: implementing additional reasoning into an efficient Look-ahead SAT solver, 345\nJärvisalo, 2012, Finding efficient circuits for ensemble computation, 369\nJeroslow, 1990, Solving propositional satisfiability problems, Ann. Math. Artif. Intell., 1, 167, 10.1007\u002FBF01531077\nKatsirelos, 2012, Eigenvector centrality in industrial SAT instances, 348\nKautz, 2003, Ten challenges redux: recent progress in propositional reasoning and search, 1\nKautz, 2007, The state of SAT, Discrete Appl. Math., 155, 1514, 10.1016\u002Fj.dam.2006.10.004\nKochemazov, 2019, MapleLCMDistChronoBT-DL, duplicate learnts heuristic-aided solvers at the SAT Race 2019, 24\nKrioukov, 2009, Curvature and temperature of complex networks, Phys. Rev. E, 80, 10.1103\u002FPhysRevE.80.035101\nLiang, 2016, Learning rate based branching heuristic for SAT solvers, vol. 9710, 123\nMarques-Silva, 1999, The impact of branching heuristics in propositional satisfiability algorithms, vol. 1695, 62\nMoskewicz, 2001, Chaff: engineering an efficient sat solver, 530\nMull, 2016, On the hardness of SAT with community structure, 141\nOmelchenko\nPapadopoulos, 2012, Popularity versus similarity in growing networks, Nature, 489, 537, 10.1038\u002Fnature11459\nSelman, 1997, Ten challenges in propositional reasoning and search, 50",{"VOID":656},"10.1016\u002Fj.artint.2021.103537","2024-05-16T01:36:19.165+00:00","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0004370221000886",[660,677],{"id":661,"sortIndex":19,"researcher":18,"roles":662,"affiliations":663,"properties":672,"displayName":674,"givenName":18,"familyName":18},"a7f4398c-60cc-482e-ba17-6bd8b2b4c6cc",[107],[664],{"id":665,"sortIndex":19,"affiliation":666,"properties":18},"40919ce7-c103-4d9c-b3a2-9e25d9a367e5",{"id":665,"createTime":18,"updateTime":18,"relativeEntities":667,"slug":18,"properties":668,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":671,"statistic":18},[],{"title":669},{"VI":670},"Department of Computer Science and Artificial Intelligence (DECSAI), Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada (UGR), Spain",[],{"title":673,"gsAuthor":675},{"VI":674},"Jesús Giráldez-Cru",{"VOID":676},"[\"RHode6gAAAAJ\"]",{"id":678,"sortIndex":238,"researcher":18,"roles":679,"affiliations":680,"properties":689,"displayName":691,"givenName":18,"familyName":18},"2eba8feb-7387-46f2-a7f6-7b9d4d23a669",[107],[681],{"id":682,"sortIndex":19,"affiliation":683,"properties":18},"9b995a93-4ac1-485c-8b27-1a0f4f64f0c6",{"id":682,"createTime":18,"updateTime":18,"relativeEntities":684,"slug":18,"properties":685,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":688,"statistic":18},[],{"title":686},{"VI":687},"Artificial Intelligence Research Institute (IIIA-CSIC), Campus UAB, Bellaterra, Spain",[],{"title":690,"gsAuthor":692},{"VI":691},"Jordi Levy",{"VOID":693},"[\"BYtNcVIAAAAJ\"]",{"url":658,"publisher":695,"properties":730},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":696,"slug":10,"properties":697,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":700,"manageAffiliations":709,"indexDatabases":715,"url":18,"thumbnailPath":18,"statistic":18,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"issn":698,"title":699},{"VOID":13},{"EN":15},[701,705],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":702,"label":703,"description":704,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":15},{},{"id":27,"createTime":18,"updateTime":18,"relativeEntities":706,"label":707,"description":708,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":30},{},[710],{"id":34,"createTime":18,"updateTime":18,"relativeEntities":711,"slug":18,"properties":712,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":714,"statistic":18},[],{"title":713},{"EN":38},[],[716,723],{"id":42,"indexDatabase":717,"url":55,"indexYears":18,"academicFieldIds":722,"indexDatabaseRanking":18},{"id":44,"createTime":18,"updateTime":18,"relativeEntities":718,"label":719,"description":720,"key":51,"publicationTags":721,"standard":18},[],{"EN":47,"VI":47},{"EN":49,"VI":50},[53,54],[57],{"id":59,"indexDatabase":724,"url":70,"indexYears":71,"academicFieldIds":729,"indexDatabaseRanking":75},{"id":61,"createTime":18,"updateTime":18,"relativeEntities":725,"label":726,"description":727,"key":67,"publicationTags":728,"standard":18},[],{"EN":64,"VI":64},{"EN":64,"VI":66},[69],[73,74],{"pages":731,"volume":733},{"VOID":732},"103537",{"VOID":734},"299",{"total":19,"publishYear":736,"statisticByYear":737},2021,{},"2021-10-01","2026-07-22T16:31:13.274+00:00",[53,75],{"id":742,"createTime":743,"updateTime":744,"relativeEntities":745,"slug":746,"properties":747,"entityType":96,"verifyStatus":97,"verifyTime":756,"verifyNote":99,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":757,"fullTextUrl":18,"authors":758,"publicationType":122,"publisherRelationship":791,"citationCount":18,"citationInfo":18,"publishDate":832,"publishYear":833,"citationAnalyzeStatus":17,"lastCitationAnalyze":744,"indexDatabases":834,"openAccess":18,"references":18,"isForceReanalyzing":200},"895958eb-9843-4e7d-815d-219fe346d3b1","2023-12-27T04:23:36.481+00:00","2026-07-22T12:48:59.673+00:00",[],"Higher-order-Petri-net-models-based-on-artificial-neural-networks",{"title":748,"gsPaper":750,"references":752,"doi":754},{"EN":749},"Higher-order Petri net models based on artificial neural networks",{"VOID":751},"[\"18188033075506282689\"]",{"VOID":753},"Ahson, 1995, Petri net models of fuzzy neural networks, IEEE Trans. Syst. Man Cybern., 25, 926, 10.1109\u002F21.384255\nAmari, 1991, Dualistic geometry of the manifold of higher-order neurons, Neural Networks, 4, 443, 10.1016\u002F0893-6080(91)90040-C\nGiles, 1987, Learning, invariance, and generalization in high-order neural networks, Appl. Optics, 26, 4972, 10.1364\u002FAO.26.004972\nHabib, 1990, Neuron type processor modelling using a timed Petri net, IEEE Trans. Neural Networks, 1, 282, 10.1109\u002F72.80264\nHaykin, 1994\nJ.Y. Li and T.W.S. Chow, Functional approximation of higher-order neural networks, J. Intell. Syst. (to appear).\nLloyd, 1984\nMurata, 1989, Petri nets: properties, analyses and applications, 77, 541\nPeterka, 1989, Proof procedure and answer extraction in Petri net model of logic programs, IEEE Trans. Softw. Eng., 15, 209, 10.1109\u002F32.21746\nVenkatesh, 1993, A high level Petri net model of olfactory bulb, 766",{"VOID":755},"10.1016\u002Fs0004-3702(96)00048-3","2024-06-25T18:52:37.775+00:00","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0004370296000483",[759,776],{"id":760,"sortIndex":19,"researcher":18,"roles":761,"affiliations":762,"properties":771,"displayName":773,"givenName":18,"familyName":18},"4b4b0fe3-33fb-49a9-931f-5aecb3e929bf",[107],[763],{"id":764,"sortIndex":19,"affiliation":765,"properties":18},"1d30f90c-debd-4c92-afec-07ad1037efdf",{"id":764,"createTime":18,"updateTime":18,"relativeEntities":766,"slug":18,"properties":767,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":770,"statistic":18},[],{"title":768},{"VI":769},"Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong",[],{"title":772,"gsAuthor":774},{"VI":773},"Tommy W.S. Chow",{"VOID":775},"[\"rEboT4IAAAAJ\"]",{"id":777,"sortIndex":238,"researcher":18,"roles":778,"affiliations":779,"properties":786,"displayName":788,"givenName":18,"familyName":18},"7616fd73-b55e-4fb2-b368-c2693e6e282e",[107],[780],{"id":764,"sortIndex":19,"affiliation":781,"properties":18},{"id":764,"createTime":18,"updateTime":18,"relativeEntities":782,"slug":18,"properties":783,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":785,"statistic":18},[],{"title":784},{"VI":769},[],{"title":787,"gsAuthor":789},{"VI":788},"Jin-Yan Li",{"VOID":790},"[\"5XCuYTgAAAAJ\"]",{"url":757,"publisher":792,"properties":827},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":793,"slug":10,"properties":794,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":797,"manageAffiliations":806,"indexDatabases":812,"url":18,"thumbnailPath":18,"statistic":18,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"issn":795,"title":796},{"VOID":13},{"EN":15},[798,802],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":799,"label":800,"description":801,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":15},{},{"id":27,"createTime":18,"updateTime":18,"relativeEntities":803,"label":804,"description":805,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":30},{},[807],{"id":34,"createTime":18,"updateTime":18,"relativeEntities":808,"slug":18,"properties":809,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":811,"statistic":18},[],{"title":810},{"EN":38},[],[813,820],{"id":42,"indexDatabase":814,"url":55,"indexYears":18,"academicFieldIds":819,"indexDatabaseRanking":18},{"id":44,"createTime":18,"updateTime":18,"relativeEntities":815,"label":816,"description":817,"key":51,"publicationTags":818,"standard":18},[],{"EN":47,"VI":47},{"EN":49,"VI":50},[53,54],[57],{"id":59,"indexDatabase":821,"url":70,"indexYears":71,"academicFieldIds":826,"indexDatabaseRanking":75},{"id":61,"createTime":18,"updateTime":18,"relativeEntities":822,"label":823,"description":824,"key":67,"publicationTags":825,"standard":18},[],{"EN":64,"VI":64},{"EN":64,"VI":66},[69],[73,74],{"pages":828,"volume":830},{"VOID":829},"289-300",{"VOID":831},"92","1997-05-01",1997,[53,75],{"id":836,"createTime":837,"updateTime":838,"relativeEntities":839,"slug":840,"properties":841,"entityType":96,"verifyStatus":97,"verifyTime":850,"verifyNote":99,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":851,"fullTextUrl":18,"authors":852,"publicationType":122,"publisherRelationship":906,"citationCount":947,"citationInfo":948,"publishDate":952,"publishYear":949,"citationAnalyzeStatus":17,"lastCitationAnalyze":838,"indexDatabases":953,"openAccess":18,"references":18,"isForceReanalyzing":200},"0e59edea-7b01-4519-812d-f7ec29ec8a71","2023-12-27T18:00:38.380+00:00","2026-07-20T16:46:14.221+00:00",[],"Better-bounds-on-the-adaptivity-gap-of-influence-maximization-under-full-adoption-feedback",{"title":842,"gsPaper":844,"references":846,"doi":848},{"EN":843},"Better bounds on the adaptivity gap of influence maximization under full-adoption feedback",{"VOID":845},"[\"11370697400096682323\"]",{"VOID":847},"Adamczyk, 2015, Improved approximation algorithms for stochastic matching, 1\nAnderson, 1992\nAsadpour, 2016, Maximizing stochastic monotone submodular functions, Manag. Sci., 62, 2374, 10.1287\u002Fmnsc.2015.2254\nBadanidiyuru, 2016, Locally adaptive optimization: adaptive seeding for monotone submodular functions, 414\nBarabási, 1999, Emergence of scaling in random networks, Science, 286, 509, 10.1126\u002Fscience.286.5439.509\nBorgs, 2014, Maximizing social influence in nearly optimal time, 946\nBradac, 2019, (Near) optimal adaptivity gaps for stochastic multi-value probing\nCălinescu, 2011, Maximizing a monotone submodular function subject to a matroid constraint, SIAM J. Comput., 40, 1740, 10.1137\u002F080733991\nCautis, 2019, Adaptive influence maximization, 3185\nChen, 2009, Approximating matches made in heaven, 266\nChen, 2011, Influence maximization in social networks when negative opinions may emerge and propagate, 379\nChen, 2013, Information and Influence Propagation in Social Networks\nChen, 2019, On adaptivity gaps of influence maximization under the independent cascade model with full-adoption feedback\nChen, 2022, Adaptive greedy versus non-adaptive greedy for influence maximization, J. Artif. Intell. Res., 74, 303, 10.1613\u002Fjair.1.12997\nChen, 2010, Scalable influence maximization for prevalent viral marketing in large-scale social networks, 1029\nD'Angelo, 2021, Better bounds on the adaptivity gap of influence maximization under full-adoption feedback, 12069\nD'Angelo, 2021, Improved approximation factor for adaptive influence maximization via simple greedy strategies\nDomingos, 2001, Mining the network value of customers, 57\nFujii, 2019, Beyond adaptive submodularity: approximation guarantees of greedy policy with adaptive submodularity ratio, 2042\nGoldberg, 2013, The diffusion of networking technologies, 1577\nGolovin, 2011, Adaptive submodularity: theory and applications in active learning and stochastic optimization, J. Artif. Intell. Res., 42, 427\nGupta, 2016, Algorithms and adaptivity gaps for stochastic probing, 1731\nGupta, 2017, Adaptivity gaps for stochastic probing: submodular and XOS functions, 1688\nHan, 2018, Efficient algorithms for adaptive influence maximization, Proc. VLDB Endow., 11, 1029, 10.14778\u002F3213880.3213883\nHuang, 2020, Efficient approximation algorithms for adaptive influence maximization, VLDB J., 29, 1385, 10.1007\u002Fs00778-020-00615-8\nKempe, 2003, Maximizing the spread of influence through a social network, 137\nKempe, 2015, Maximizing the spread of influence through a social network, Theory Comput., 11, 105, 10.4086\u002Ftoc.2015.v011a004\nLeskovec, 2007, Cost-effective outbreak detection in networks, 420\nLi, 2018, Influence maximization on social graphs: a survey, IEEE Trans. Knowl. Data Eng., 30, 1852, 10.1109\u002FTKDE.2018.2807843\nLiang, 2022, Multi-batches revenue maximization for competitive products over online social network, J. Netw. Comput. Appl., 201, 10.1016\u002Fj.jnca.2022.103357\nLowalekar, 2016, Robust influence maximization, 1395\nLu, 2017, Solution of Bharathi-Kempe-Salek conjecture for influence maximization on arborescence, J. Comb. Optim., 33, 803, 10.1007\u002Fs10878-016-0006-z\nMihara, 2015, Influence maximization problem for unknown social networks, 1539\nNorris, 1997\nPastor-Satorras, 2015, Epidemic processes in complex networks, Rev. Mod. Phys., 87, 925, 10.1103\u002FRevModPhys.87.925\nPeng, 2019, Adaptive influence maximization with myopic feedback, vol. 32, 5575\nRichardson, 2002, Mining knowledge-sharing sites for viral marketing, 61\nRubinstein, 2015, Approximability of adaptive seeding under knapsack constraints, 797\nSalha, 2018, Adaptive submodular influence maximization with myopic feedback, 455\nSchoenebeck, 2019, Influence maximization on undirected graphs: towards closing the (1-1\u002Fe) gap, 423\nSeeman, 2013, Adaptive seeding in social networks, 459\nSinger, 2016, Influence maximization through adaptive seeding, ACM SIGecom Exch., 15, 32, 10.1145\u002F2994501.2994503\nSun, 2018, Multi-round influence maximization, 2249\nTang, 2019, Efficient approximation algorithms for adaptive seed minimization, 1096\nTang, 2014, Influence maximization: near-optimal time complexity meets practical efficiency, 75\nTong, 2022, On adaptive influence maximization under general feedback models, IEEE Trans. Emerg. Top. Comput., 10, 463, 10.1109\u002FTETC.2020.3031057\nTong, 2021, Time-constrained adaptive influence maximization, IEEE Trans. Comput. Soc. Syst., 8, 33, 10.1109\u002FTCSS.2020.3032616\nTong, 2017, Adaptive influence maximization in dynamic social networks, IEEE\u002FACM Trans. Netw., 25, 112, 10.1109\u002FTNET.2016.2563397\nVaswani\nYuan, 2017, No time to observe: adaptive influence maximization with partial feedback, 3908\nZhang, 2022, Adaptive influence maximization under fixed observation time-step, Theor. Comput. Sci., 928, 104, 10.1016\u002Fj.tcs.2022.06.018",{"VOID":849},"10.1016\u002Fj.artint.2023.103895","2024-05-29T00:48:55.830+00:00","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0004370223000413",[853,870,883],{"id":854,"sortIndex":19,"researcher":18,"roles":855,"affiliations":856,"properties":865,"displayName":867,"givenName":18,"familyName":18},"20f7e29c-c6ef-418a-9e21-7f3f03282d28",[107],[857],{"id":858,"sortIndex":19,"affiliation":859,"properties":18},"6071a42e-9a43-472e-aa06-e92a808e75a8",{"id":858,"createTime":18,"updateTime":18,"relativeEntities":860,"slug":18,"properties":861,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":864,"statistic":18},[],{"title":862},{"VI":863},"Gran Sasso Science Institute, L’Aquila, Italy",[],{"title":866,"gsAuthor":868},{"VI":867},"Gianlorenzo D'Angelo",{"VOID":869},"[\"FlZ-5sMAAAAJ\"]",{"id":871,"sortIndex":238,"researcher":18,"roles":872,"affiliations":873,"properties":880,"displayName":882,"givenName":18,"familyName":18},"e722eac7-4282-4657-950e-6caef6287198",[107],[874],{"id":858,"sortIndex":19,"affiliation":875,"properties":18},{"id":858,"createTime":18,"updateTime":18,"relativeEntities":876,"slug":18,"properties":877,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":879,"statistic":18},[],{"title":878},{"VI":863},[],{"title":881},{"VI":882},"Debashmita Poddar",{"id":884,"sortIndex":168,"researcher":18,"roles":885,"affiliations":886,"properties":901,"displayName":903,"givenName":18,"familyName":18},"d0099552-6d21-4d64-a83a-04bff14ec67a",[107],[887,895],{"id":888,"sortIndex":19,"affiliation":889,"properties":18},"639b7557-ba62-417c-b275-e5c206b0b95b",{"id":888,"createTime":18,"updateTime":18,"relativeEntities":890,"slug":18,"properties":891,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":894,"statistic":18},[],{"title":892},{"VI":893},"University of Salento, Lecce, Italy",[],{"id":858,"sortIndex":238,"affiliation":896,"properties":18},{"id":858,"createTime":18,"updateTime":18,"relativeEntities":897,"slug":18,"properties":898,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":900,"statistic":18},[],{"title":899},{"VI":863},[],{"title":902,"gsAuthor":904},{"VI":903},"Cosimo Vinci",{"VOID":905},"[\"myrdajsAAAAJ\"]",{"url":851,"publisher":907,"properties":942},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":908,"slug":10,"properties":909,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":912,"manageAffiliations":921,"indexDatabases":927,"url":18,"thumbnailPath":18,"statistic":18,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"issn":910,"title":911},{"VOID":13},{"EN":15},[913,917],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":914,"label":915,"description":916,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":15},{},{"id":27,"createTime":18,"updateTime":18,"relativeEntities":918,"label":919,"description":920,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":30},{},[922],{"id":34,"createTime":18,"updateTime":18,"relativeEntities":923,"slug":18,"properties":924,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":926,"statistic":18},[],{"title":925},{"EN":38},[],[928,935],{"id":42,"indexDatabase":929,"url":55,"indexYears":18,"academicFieldIds":934,"indexDatabaseRanking":18},{"id":44,"createTime":18,"updateTime":18,"relativeEntities":930,"label":931,"description":932,"key":51,"publicationTags":933,"standard":18},[],{"EN":47,"VI":47},{"EN":49,"VI":50},[53,54],[57],{"id":59,"indexDatabase":936,"url":70,"indexYears":71,"academicFieldIds":941,"indexDatabaseRanking":75},{"id":61,"createTime":18,"updateTime":18,"relativeEntities":937,"label":938,"description":939,"key":67,"publicationTags":940,"standard":18},[],{"EN":64,"VI":64},{"EN":64,"VI":66},[69],[73,74],{"pages":943,"volume":945},{"VOID":944},"103895",{"VOID":946},"318",19,{"total":947,"publishYear":949,"statisticByYear":950},2023,{"2020":168,"2022":273,"2023":273,"2024":951,"2025":273,"2026":168},6,"2023-05-01",[53,75],{"id":955,"createTime":956,"updateTime":957,"relativeEntities":958,"slug":959,"properties":960,"entityType":96,"verifyStatus":97,"verifyTime":967,"verifyNote":99,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":968,"fullTextUrl":18,"authors":969,"publicationType":122,"publisherRelationship":985,"citationCount":19,"citationInfo":1026,"publishDate":1029,"publishYear":1027,"citationAnalyzeStatus":197,"lastCitationAnalyze":1030,"indexDatabases":1031,"openAccess":18,"references":1032,"isForceReanalyzing":200},"ce1223c3-5a82-4e02-8046-9556718d0c0c","2024-01-12T13:11:22.954+00:00","2026-07-20T07:12:03.276+00:00",[],"An-examination-of-the-geometry-theorem-machine",{"title":961,"gsPaper":963,"doi":965},{"EN":962},"An examination of the geometry theorem machine",{"VOID":964},"[\"9434676046282511228\"]",{"VOID":966},"10.1016\u002F0004-3702(70)90005-6","2024-04-30T20:43:08.789+00:00","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002F0004370270900056",[970],{"id":971,"sortIndex":19,"researcher":18,"roles":972,"affiliations":973,"properties":982,"displayName":984,"givenName":18,"familyName":18},"177f77d4-9faa-4d96-b89e-937b16255825",[107],[974],{"id":975,"sortIndex":19,"affiliation":976,"properties":18},"89a941df-81f1-479a-8fc4-41ed636c82fd",{"id":975,"createTime":18,"updateTime":18,"relativeEntities":977,"slug":18,"properties":978,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":981,"statistic":18},[],{"title":979},{"VI":980},"Thomas J. Watson, Research Center, Yorktown Heights, New York USA",[],{"title":983},{"VI":984},"P.C. Gilmore",{"url":968,"publisher":986,"properties":1021},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":987,"slug":10,"properties":988,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":991,"manageAffiliations":1000,"indexDatabases":1006,"url":18,"thumbnailPath":18,"statistic":18,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"issn":989,"title":990},{"VOID":13},{"EN":15},[992,996],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":993,"label":994,"description":995,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":15},{},{"id":27,"createTime":18,"updateTime":18,"relativeEntities":997,"label":998,"description":999,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":30},{},[1001],{"id":34,"createTime":18,"updateTime":18,"relativeEntities":1002,"slug":18,"properties":1003,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1005,"statistic":18},[],{"title":1004},{"EN":38},[],[1007,1014],{"id":42,"indexDatabase":1008,"url":55,"indexYears":18,"academicFieldIds":1013,"indexDatabaseRanking":18},{"id":44,"createTime":18,"updateTime":18,"relativeEntities":1009,"label":1010,"description":1011,"key":51,"publicationTags":1012,"standard":18},[],{"EN":47,"VI":47},{"EN":49,"VI":50},[53,54],[57],{"id":59,"indexDatabase":1015,"url":70,"indexYears":71,"academicFieldIds":1020,"indexDatabaseRanking":75},{"id":61,"createTime":18,"updateTime":18,"relativeEntities":1016,"label":1017,"description":1018,"key":67,"publicationTags":1019,"standard":18},[],{"EN":64,"VI":64},{"EN":64,"VI":66},[69],[73,74],{"pages":1022,"volume":1024},{"VOID":1023},"171-187",{"VOID":1025},"1",{"total":19,"publishYear":1027,"statisticByYear":1028},1970,{},"1970-01-01","2026-07-20T07:12:03.275+00:00",[53,75],[1033,1036,1039,1045,1048,1055,1058,1061,1065,1071,1078],{"id":955,"text":1034,"url":968,"identifiers":1035},"Gilmore, 1962, An examination of the geometry theorem machine, IBM Res Report RZ-87",{"doi":966},{"id":18,"text":1037,"url":18,"identifiers":1038},"Gilmore, 1963, Meetkundige bewijzen door de computer",{},{"id":1040,"text":1041,"url":1042,"identifiers":1043},"e383a803-c50b-4425-b8ad-36c15ee25d58","Gelernter, 1958, Intelligent behavior in problem-solving machines, IBM J. R&D, 2, 336, 10.1147\u002Frd.24.0336","http:\u002F\u002Flink.springer.com\u002F10.1007\u002FBF02724680",{"doi":1044},"10.1007\u002FBF02724680",{"id":537,"text":1046,"url":539,"identifiers":1047},"Gelernter, 1959, Realization of a geometry theorem-proving machine",{"doi":541},{"id":18,"text":1049,"url":1050,"identifiers":1051},"Gelernter, 1959, A note on syntactic symmetry and the manipulation of formal systems by machine, Information and Control, 2, 80, 10.1016\u002FS0019-9958(59)90090-7","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fs0019-9958(59)90090-7",{"mag":1052,"openalex":1053,"doi":1054},"2086121771","W2086121771","10.1016\u002Fs0019-9958(59)90090-7",{"id":537,"text":1056,"url":539,"identifiers":1057},"Gelernter, 1960, Empirical explorations of the geometry theorem machine",{"doi":541},{"id":537,"text":1059,"url":539,"identifiers":1060},"Gelernter, 1963, Machine generated problem solving graphs, 179",{"doi":541},{"id":18,"text":1062,"url":18,"identifiers":1063},"Gilmore, 1960, A proof procedure for quantification theory: its justification and realization, IBM J., 4, 28, 10.1147\u002Frd.41.0028",{"doi":1064},"10.1147\u002Frd.41.0028",{"id":18,"text":1066,"url":1067,"identifiers":1068},"Robinson, 1967, A review of automatic theorem-proving, 1, 10.1090\u002Fpsapm\u002F019\u002F0241195","https:\u002F\u002Fdoi.org\u002F10.1090\u002Fpsapm\u002F019\u002F0241195",{"openalex":1069,"doi":1070},"W4246237914","10.1090\u002Fpsapm\u002F019\u002F0241195",{"id":18,"text":1072,"url":1073,"identifiers":1074},"Guard, 1969, Semi-automated mathematics, J. ACM, 16, 49, 10.1145\u002F321495.321500","https:\u002F\u002Fdoi.org\u002F10.1145\u002F321495.321500",{"mag":1075,"openalex":1076,"doi":1077},"1985789487","W1985789487","10.1145\u002F321495.321500",{"id":537,"text":1079,"url":539,"identifiers":1080},"Tarski, 1957, A Decision Method for Elementary Algebra and Geometry, 63",{"doi":541},{"id":1082,"createTime":1083,"updateTime":1084,"relativeEntities":1085,"slug":1086,"properties":1087,"entityType":96,"verifyStatus":97,"verifyTime":1096,"verifyNote":99,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":1097,"fullTextUrl":18,"authors":1098,"publicationType":122,"publisherRelationship":1131,"citationCount":19,"citationInfo":1172,"publishDate":1174,"publishYear":949,"citationAnalyzeStatus":197,"lastCitationAnalyze":1084,"indexDatabases":1175,"openAccess":18,"references":18,"isForceReanalyzing":200},"c4a466d5-46bf-4953-8161-06d60992d96d","2024-01-05T22:22:45.115+00:00","2026-07-19T11:16:48.227+00:00",[],"Introspective-perception-for-mobile-robots",{"title":1088,"gsPaper":1090,"references":1092,"doi":1094},{"EN":1089},"Introspective perception for mobile robots",{"VOID":1091},"[\"7021751158541818734\"]",{"VOID":1093},"Kaess, 2009, Covariance recovery from a square root information matrix for data association, Robot. Auton. Syst., 57, 1198, 10.1016\u002Fj.robot.2009.06.008\nUrtasun, 2006, 3D people tracking with Gaussian process dynamical models, 238\nRabiee, 2019, IVOA: introspective vision for obstacle avoidance, 1230\nRabiee, 2020, Iv-slam: introspective vision for simultaneous localization and mapping\nPereira, 2013, Risk-aware path planning for autonomous underwater vehicles using predictive ocean models, J. Field Robot., 30, 741, 10.1002\u002Frob.21472\nKapoor, 2007, Active learning with Gaussian processes for object categorization, 1\nLiu, 2019, Universal adversarial perturbation via prior driven uncertainty approximation, 2941\nPandey, 2015, Automatic extrinsic calibration of vision and lidar by maximizing mutual information, J. Field Robot., 32, 696, 10.1002\u002Frob.21542\nZhang, 2005, Dynamic Cramer-Rao bound for target tracking in clutter, IEEE Trans. Aerosp. Electron. Syst., 41, 1154, 10.1109\u002FTAES.2005.1561880\nSadat, 2014, Feature-rich path planning for robust navigation of MAVs with mono-SLAM, 3870\nMostegel, 2014, Active monocular localization: towards autonomous monocular exploration for multirotor MAVs, 3848\nRasmussen, 2003, Gaussian processes in machine learning, 63\nQuinonero-Candela, 2005, A unifying view of sparse approximate Gaussian process regression, J. Mach. Learn. Res., 6, 1939\nGhahramani, 1997, Learning dynamic Bayesian networks, 168\nLee, 2018, Deep neural networks as Gaussian processes\nDusenberry, 2020, Efficient and scalable Bayesian neural nets with rank-1 factors, 2782\nGal, 2016, Dropout as a Bayesian approximation: representing model uncertainty in deep learning, 1050\nGrimmett, 2016, Introspective classification for robot perception, Int. J. Robot. Res., 35, 743, 10.1177\u002F0278364915587924\nLakshminarayanan, 2017, Simple and scalable predictive uncertainty estimation using deep ensembles, 6405\nY. Ovadia, E. Fertig, J. Ren, Z. Nado, D. Sculley, S. Nowozin, J.V. Dillon, B. Lakshminarayanan, J. Snoek, Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift, 2019.\nGoodfellow, 2014, Generative adversarial nets, Adv. Neural Inf. Process. Syst., 27\nVincent, 2008, Extracting and composing robust features with denoising autoencoders, 1096\nKingma\nAn, 2015, Variational autoencoder based anomaly detection using reconstruction probability, 1\nDesai, 2017, Combining model checking and runtime verification for safe robotics, 172\nGhosh, 2016, Diagnosis and repair for synthesis from signal temporal logic specifications, 31\nBalakrishnan, 2021, Percemon: online monitoring for perception systems, 297\nBalakrishnan, 2019, Specifying and evaluating quality metrics for vision-based perception systems, 1433\nMitsch, 2017, Formal verification of obstacle avoidance and navigation of ground robots, Int. J. Robot. Res., 36, 1312, 10.1177\u002F0278364917733549\nZhang, 2014, Predicting failures of vision systems, 3566\nDaftry, 2016, Introspective perception: learning to predict failures in vision systems, 1743\nGurău, 2018, Learn from experience: probabilistic prediction of perception performance to avoid failure, Int. J. Robot. Res., 37, 981, 10.1177\u002F0278364917730603\nVega-Brown, 2013, Cello: a fast algorithm for covariance estimation, 3160\nStronger, 2006, Towards autonomous sensor and actuator model induction on a mobile robot, Connect. Sci., 18, 97, 10.1080\u002F09540090600768690\nHoltz, 2017, Automatic extrinsic calibration of depth sensors with ambiguous environments and restricted motion, 2235\nSchonberger, 2016, Structure-from-motion revisited, 4104\nKundu, 2022, Panoptic neural fields: a semantic object-aware neural scene representation, 12871\nThrun, 2005\nPepy, 2006, Safe path planning in an uncertain-configuration space using RRT, 5376\nOstafew, 2016, Robust constrained learning-based NMPC enabling reliable mobile robot path tracking, Int. J. Robot. Res., 35, 1547, 10.1177\u002F0278364916645661\nBarbosa, 2021, Risk-aware motion planning in partially known environments\nBlackmore, 2011, Chance-constrained optimal path planning with obstacles, IEEE Trans. Robot., 27, 1080, 10.1109\u002FTRO.2011.2161160\nJasour, 2019, Risk contours map for risk bounded motion planning under perception uncertainties\nRabiee, 2022, Competence-aware path planning via introspective perception, IEEE Robot. Autom. Lett., 7, 3218, 10.1109\u002FLRA.2022.3145517\nWang, 2017, DeepVO: towards end-to-end visual odometry with deep recurrent convolutional neural networks, 2043\nParisotto, 2018, Global pose estimation with an attention-based recurrent network, 237\nTriggs, 1999, Bundle adjustment–a modern synthesis, 298\nBlack, 1996, On the unification of line processes, outlier rejection, and robust statistics with applications in early vision, Int. J. Comput. Vis., 19, 57, 10.1007\u002FBF00131148\nBarron, 2019, A general and adaptive robust loss function, 4331\nFischler, 1981, Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography, Commun. ACM, 24, 381, 10.1145\u002F358669.358692\nForster, 2014, SVO: fast semi-direct monocular visual odometry, 15\nYi, 2018, Learning to find good correspondences, 2666\nSun, 2020, Acne: attentive context normalization for robust permutation-equivariant learning, 11286\nTriggs, 2000, Bundle adjustment—a modern synthesis, 298\nZhou, 2017, Scene parsing through ADE20K dataset, 633\nSandler, 2018, MobileNetV2: inverted residuals and linear bottlenecks, 4510\nShan, 2018, Lego-loam: lightweight and ground-optimized lidar odometry and mapping on variable terrain, 4758\nKrizhevsky, 2012, Imagenet classification with deep convolutional neural networks, 1097\nMur-Artal, 2017, ORB-SLAM2: an open-source slam system for monocular, stereo, and RGB-d cameras, IEEE Trans. Robot., 33, 1255, 10.1109\u002FTRO.2017.2705103\nGhosh, 2017, Joint perception and planning for efficient obstacle avoidance using stereo vision, 1026\nZhang, 2019, GA-Net: guided aggregation net for end-to-end stereo matching, 185\nGeiger, 2012, Are we ready for autonomous driving? The KITTI vision benchmark suite, 3354\nBurri, 2016, The EuRoC micro aerial vehicle datasets, Int. J. Robot. Res., 35, 1157, 10.1177\u002F0278364915620033\nShi\nShah, 2018, AirSim: high-fidelity visual and physical simulation for autonomous vehicles, 621\nBrunner, 2013, Selective combination of visual and thermal imaging for resilient localization in adverse conditions: day and night, smoke and fire, J. Field Robot., 30, 641, 10.1002\u002Frob.21464\nSchubert, 2018, The TUM VI benchmark for evaluating visual-inertial odometry, 1680\nMaaten, 2008, Visualizing data using t-SNE, J. Mach. Learn. Res., 9, 2579\nJulier, 2004, Unscented filtering and nonlinear estimation, Proc. IEEE, 92, 401, 10.1109\u002FJPROC.2003.823141\nBajcsy, 1988, Active perception, Proc. IEEE, 76, 966, 10.1109\u002F5.5968\nKrainin, 2011, Autonomous generation of complete 3D object models using next best view manipulation planning",{"VOID":1095},"10.1016\u002Fj.artint.2023.103999","2024-06-26T11:07:29.017+00:00","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0004370223001455",[1099,1116],{"id":1100,"sortIndex":19,"researcher":18,"roles":1101,"affiliations":1102,"properties":1111,"displayName":1113,"givenName":18,"familyName":18},"7b45f9dd-7ab7-4220-b3a7-14dc6304cffb",[107],[1103],{"id":1104,"sortIndex":19,"affiliation":1105,"properties":18},"fed70c0d-b40e-4978-8a4f-b7aaedbbcda9",{"id":1104,"createTime":18,"updateTime":18,"relativeEntities":1106,"slug":18,"properties":1107,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1110,"statistic":18},[],{"title":1108},{"VI":1109},"The Department of Computer Science, The University of Texas at Austin, Austin TX 78712, United States of America",[],{"title":1112,"gsAuthor":1114},{"VI":1113},"Sadegh Rabiee",{"VOID":1115},"[\"QLFhfn0AAAAJ\"]",{"id":1117,"sortIndex":238,"researcher":18,"roles":1118,"affiliations":1119,"properties":1126,"displayName":1128,"givenName":18,"familyName":18},"26bc4395-e6c4-4637-a049-ede813dd90de",[107],[1120],{"id":1104,"sortIndex":19,"affiliation":1121,"properties":18},{"id":1104,"createTime":18,"updateTime":18,"relativeEntities":1122,"slug":18,"properties":1123,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1125,"statistic":18},[],{"title":1124},{"VI":1109},[],{"title":1127,"gsAuthor":1129},{"VI":1128},"Joydeep Biswas",{"VOID":1130},"[\"f28F1YUAAAAJ\"]",{"url":1097,"publisher":1132,"properties":1167},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1133,"slug":10,"properties":1134,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":1137,"manageAffiliations":1146,"indexDatabases":1152,"url":18,"thumbnailPath":18,"statistic":18,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"issn":1135,"title":1136},{"VOID":13},{"EN":15},[1138,1142],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":1139,"label":1140,"description":1141,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":15},{},{"id":27,"createTime":18,"updateTime":18,"relativeEntities":1143,"label":1144,"description":1145,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":30},{},[1147],{"id":34,"createTime":18,"updateTime":18,"relativeEntities":1148,"slug":18,"properties":1149,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1151,"statistic":18},[],{"title":1150},{"EN":38},[],[1153,1160],{"id":42,"indexDatabase":1154,"url":55,"indexYears":18,"academicFieldIds":1159,"indexDatabaseRanking":18},{"id":44,"createTime":18,"updateTime":18,"relativeEntities":1155,"label":1156,"description":1157,"key":51,"publicationTags":1158,"standard":18},[],{"EN":47,"VI":47},{"EN":49,"VI":50},[53,54],[57],{"id":59,"indexDatabase":1161,"url":70,"indexYears":71,"academicFieldIds":1166,"indexDatabaseRanking":75},{"id":61,"createTime":18,"updateTime":18,"relativeEntities":1162,"label":1163,"description":1164,"key":67,"publicationTags":1165,"standard":18},[],{"EN":64,"VI":64},{"EN":64,"VI":66},[69],[73,74],{"pages":1168,"volume":1170},{"VOID":1169},"103999",{"VOID":1171},"324",{"total":19,"publishYear":949,"statisticByYear":1173},{},"2023-11-01",[53,75],{"id":1177,"createTime":1178,"updateTime":1179,"relativeEntities":1180,"slug":1181,"properties":1182,"entityType":96,"verifyStatus":97,"verifyTime":1191,"verifyNote":99,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":1192,"fullTextUrl":18,"authors":1193,"publicationType":122,"publisherRelationship":1224,"citationCount":19,"citationInfo":1265,"publishDate":1268,"publishYear":1266,"citationAnalyzeStatus":197,"lastCitationAnalyze":1179,"indexDatabases":1269,"openAccess":18,"references":18,"isForceReanalyzing":200},"50cb6b46-3b18-4443-80fd-19bfd22546e8","2024-01-13T11:35:50.907+00:00","2026-07-18T03:56:00.996+00:00",[],"Temporal-reasoning-about-fuzzy-intervals",{"title":1183,"gsPaper":1185,"references":1187,"doi":1189},{"EN":1184},"Temporal reasoning about fuzzy intervals",{"VOID":1186},"[\"13071858385733688631\"]",{"VOID":1188},"Allen, 1983, Maintaining knowledge about temporal intervals, Communications of the ACM, 26, 832, 10.1145\u002F182.358434\nJ. Allen, Planning as temporal reasoning, in: Proceedings of the Second International Conference on Principles of Knowledge Representation and Reasoning, 1991\nE. André, T. Rist, Coping with temporal constraints in multimedia presentation planning, in: Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), 1996\nBadaloni, 2006, The algebra IAfuz: a framework for qualitative fuzzy temporal reasoning, Artificial Intelligence, 170, 872, 10.1016\u002Fj.artint.2006.04.001\nBarro, 1994, A model and a language for the fuzzy representation and handling of time, Fuzzy Sets and Systems, 61, 153, 10.1016\u002F0165-0114(94)90231-3\nBarzilay, 2002, Inferring strategies for sentence ordering in multidocument news summarization, Journal of Artificial Intelligence Research, 17, 35, 10.1613\u002Fjair.991\nBodenhofer, 1999, A new approach to fuzzy orderings, Tatra Mountains Mathematical Publications, 16, 21\nA. Bosch, M. Torres, R. Marin, Reasoning with disjunctive fuzzy temporal constraint networks, in: Proceedings of the 9th International Symposium on Temporal Representation and Reasoning, 2002\nBry, 2003, On reasoning on time and location on the web, vol. 2901\nM. Buchanan, P. Zellweger, Scheduling multimedia documents using temporal constraints, in: Proceedings of the Third International Workshop on Network and Operating System Support for Digital Audio and Video, 1992\nCohn, 1996, The ‘egg-yolk’ representation of regions with indeterminate boundaries\nDechter, 1991, Temporal constraint networks, Artificial Intelligence, 49, 61, 10.1016\u002F0004-3702(91)90006-6\nDrakengren, 1997, Eight maximal tractable subclasses of Allen's algebra with metric time, Journal of Artificial Intelligence Research, 7, 25, 10.1613\u002Fjair.340\nDrakengren, 1997, Twenty-one large tractable subclasses of Allen's algebra, Artificial Intelligence, 93, 297, 10.1016\u002FS0004-3702(97)00021-0\nDubois, 1983, Ranking fuzzy numbers in the setting of possibility theory, Information Sciences, 30, 183, 10.1016\u002F0020-0255(83)90025-7\nDubois, 1989, Processing fuzzy temporal knowledge, IEEE Transactions on Systems, Man, and Cybernetics, 19, 729, 10.1109\u002F21.35337\nA. El-Kholy, B. Richards, Temporal and resource reasoning in planning: the parcPLAN approach, in: Proceedings of the 12th European Conference on Artificial Intelligence (ECAI-96), 1996\nErfle, 1993, Specification of temporal constraints in multimedia documents using HyTime, Electronic Publishing, 6, 397\nFox, 2003, PDDL2.1: an extension to PDDL for expressing temporal planning domains, Journal of Artificial Intelligence Research, 20, 61, 10.1613\u002Fjair.1129\nA. Gerevini, M. Cristani, On finding a solution in temporal constraint satisfaction problems, in: Proceedings of the International Joint Conference on Artificial Intelligence, 1997\nH. Guesgen, J. Hertzberg, A. Philpott, Towards implementing fuzzy Allen relations, in: Proceedings of the ECAI-94 Workshop on Spatial and Temporal Reasoning, 1994\nS. Harabagiu, C. Bejan, Question answering based on temporal inference, in: AAAI-2005 Workshop on Inference for Textual Question Answering, 2005\nJonsson, 1998, A unifying approach to temporal constraint reasoning, Artificial Intelligence, 102, 143, 10.1016\u002FS0004-3702(98)00031-9\nKalczynski, 2005, Temporal document retrieval model for business news archives, Information Processing and Management, 41, 635, 10.1016\u002Fj.ipm.2004.01.002\nH. Kautz, P. Ladkin, Integrating metric and qualitative temporal reasoning, in: Proceedings of the Ninth National Conference on Artificial Intelligence (AAAI-91), 1991\nL. Khatib, P. Morris, R. Morris, F. Rossi, Temporal constraint reasoning with preferences, in: Proceedings of the 17th International Joint Conference on Artificial Intelligence, 2001\nKoubarakis, 2001, Tractable disjunctions of linear constraints: basic results and applications to temporal reasoning, Theoretical Computer Science, 266, 311, 10.1016\u002FS0304-3975(00)00177-8\nKrokhin, 2003, Reasoning about temporal relations: The tractable subalgebras of Allen's interval algebra, Journal of the ACM, 50, 591, 10.1145\u002F876638.876639\nLapata, 2004, Proceedings of the North American chapter of the association of computational linguistics, vol. 2888\nMarín, 1994, Modelling the representation of time from a fuzzy perspective, Cybernetics and Systems, 25, 217, 10.1080\u002F01969729408902325\nMeiri, 1996, Combining qualitative and quantitative constraints in temporal reasoning, Artificial Intelligence, 87, 343, 10.1016\u002F0004-3702(95)00109-3\nD. Moldovan, C. Clark, S. Harabagiu, Temporal context representation and reasoning, in: Proceedings of the 19th International Joint Conference on Artificial Intelligence, 2005\nNagypál, 2003, A fuzzy model for representing uncertain, subjective and vague temporal knowledge in ontologies, vol. 2888\nA. Nakhimovsky, Temporal reasoning in natural language understanding: the temporal structure of the narrative, in: Third Conference of the European Chapter of the Association for Computational Linguistics, 1987\nNavarrete, 2002, On point-duration networks for temporal reasoning, Artificial Intelligence, 140, 39, 10.1016\u002FS0004-3702(02)00226-6\nNebel, 1997, Solving hard qualitative temporal reasoning problems: Evaluating the efficiency of using the ORD-Horn class, Constraints, 1, 175, 10.1007\u002FBF00137869\nNebel, 1995, Reasoning about temporal relations: a maximal tractable subset of Allen's interval algebra, Journal of the ACM, 42, 43, 10.1145\u002F200836.200848\nH. Ohlbach, Relations between fuzzy time intervals, in: Proceedings of the 11th International Symposium on Temporal Representation and Reasoning, 2004\nE. Saquete, P. Martínez-Barco, R. Muñoz, J. Vicedo, Splitting complex temporal questions for question answering systems, in: Proceedings of the 42nd Annual Meeting of the ACL, 2004\nSchockaert, 2006, Question answering with imperfect temporal information, vol. 4027\nS. Schockaert, M. De Cock, E. Kerre, Fuzzifying Allen's temporal interval relations, IEEE Transactions on Fuzzy Systems, in press\nSchockaert, 2006, Imprecise temporal interval relations, vol. 3849\nS. Schockaert, M. De Cock, E. Kerre, Qualitative temporal reasoning about vague events, in: Proceedings of the 20th International Joint Conference on Artificial Intelligence, 2007\nSontag, 1985, Real addition and the polynomial time hierarchy, Information Processing Letters, 20, 115, 10.1016\u002F0020-0190(85)90076-6\nStergiou, 2000, Backtracking algorithms for disjunctions of temporal constraints, Artificial Intelligence, 120, 81, 10.1016\u002FS0004-3702(00)00019-9\nTsamardinos, 2003, Efficient solution techniques for disjunctive temporal reasoning problems, Artificial Intelligence, 151, 43, 10.1016\u002FS0004-3702(03)00113-9\nZacks, 2001, Event structure in perception and conception, Psychological Bulletin, 127, 3, 10.1037\u002F0033-2909.127.1.3\nZadeh, 1965, Fuzzy sets, Information and Control, 8, 338, 10.1016\u002FS0019-9958(65)90241-X",{"VOID":1190},"10.1016\u002Fj.artint.2008.01.001","2024-05-14T08:21:41.432+00:00","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0004370208000039",[1194,1211],{"id":1195,"sortIndex":19,"researcher":18,"roles":1196,"affiliations":1197,"properties":1206,"displayName":1208,"givenName":18,"familyName":18},"99ff6829-729c-499c-9741-452fcb942fc6",[107],[1198],{"id":1199,"sortIndex":19,"affiliation":1200,"properties":18},"0c7dadc1-c3a4-404f-b05e-0c0e0452bd5e",{"id":1199,"createTime":18,"updateTime":18,"relativeEntities":1201,"slug":18,"properties":1202,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1205,"statistic":18},[],{"title":1203},{"VI":1204},"Ghent University, Department of Applied Mathematics and Computer Science, Krijgslaan 281-S9, 9000 Gent, Belgium",[],{"title":1207,"gsAuthor":1209},{"VI":1208},"Steven Schockaert",{"VOID":1210},"[\"hNCN09AAAAAJ\"]",{"id":1212,"sortIndex":238,"researcher":18,"roles":1213,"affiliations":1214,"properties":1221,"displayName":1223,"givenName":18,"familyName":18},"2b67f700-87f3-4f11-b9a5-b4b650c7217a",[107],[1215],{"id":1199,"sortIndex":19,"affiliation":1216,"properties":18},{"id":1199,"createTime":18,"updateTime":18,"relativeEntities":1217,"slug":18,"properties":1218,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1220,"statistic":18},[],{"title":1219},{"VI":1204},[],{"title":1222},{"VI":1223},"Martine De Cock",{"url":1192,"publisher":1225,"properties":1260},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1226,"slug":10,"properties":1227,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":1230,"manageAffiliations":1239,"indexDatabases":1245,"url":18,"thumbnailPath":18,"statistic":18,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"issn":1228,"title":1229},{"VOID":13},{"EN":15},[1231,1235],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":1232,"label":1233,"description":1234,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":15},{},{"id":27,"createTime":18,"updateTime":18,"relativeEntities":1236,"label":1237,"description":1238,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":30},{},[1240],{"id":34,"createTime":18,"updateTime":18,"relativeEntities":1241,"slug":18,"properties":1242,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1244,"statistic":18},[],{"title":1243},{"EN":38},[],[1246,1253],{"id":42,"indexDatabase":1247,"url":55,"indexYears":18,"academicFieldIds":1252,"indexDatabaseRanking":18},{"id":44,"createTime":18,"updateTime":18,"relativeEntities":1248,"label":1249,"description":1250,"key":51,"publicationTags":1251,"standard":18},[],{"EN":47,"VI":47},{"EN":49,"VI":50},[53,54],[57],{"id":59,"indexDatabase":1254,"url":70,"indexYears":71,"academicFieldIds":1259,"indexDatabaseRanking":75},{"id":61,"createTime":18,"updateTime":18,"relativeEntities":1255,"label":1256,"description":1257,"key":67,"publicationTags":1258,"standard":18},[],{"EN":64,"VI":64},{"EN":64,"VI":66},[69],[73,74],{"pages":1261,"volume":1263},{"VOID":1262},"1158-1193",{"VOID":1264},"172",{"total":19,"publishYear":1266,"statisticByYear":1267},2008,{},"2008-05-01",[53,75]]