{"id":"https://openalex.org/W3211388650","doi":"https://doi.org/10.1145/3472307.3484174","title":"Proposing an Inferential Model for Indebtedness Arising from Agents\u2019 Helping Behavior Using Bayesian Model","display_name":"Proposing an Inferential Model for Indebtedness Arising from Agents\u2019 Helping Behavior Using Bayesian Model","publication_year":2021,"publication_date":"2021-11-09","ids":{"openalex":"https://openalex.org/W3211388650","doi":"https://doi.org/10.1145/3472307.3484174","mag":"3211388650"},"language":"en","primary_location":{"id":"doi:10.1145/3472307.3484174","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3472307.3484174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Human-Agent Interaction","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041250385","display_name":"Masanari Ichikawa","orcid":null},"institutions":[{"id":"https://openalex.org/I1298590031","display_name":"Shizuoka University","ror":"https://ror.org/01w6wtk13","country_code":"JP","type":"education","lineage":["https://openalex.org/I1298590031"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Masanari Ichikawa","raw_affiliation_strings":["Faculty of Informatics, Shizuoka University, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Informatics, Shizuoka University, Japan","institution_ids":["https://openalex.org/I1298590031"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043574414","display_name":"Takafumi Sakamoto","orcid":"https://orcid.org/0009-0002-2367-5337"},"institutions":[{"id":"https://openalex.org/I1298590031","display_name":"Shizuoka University","ror":"https://ror.org/01w6wtk13","country_code":"JP","type":"education","lineage":["https://openalex.org/I1298590031"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takafumi Sakamoto","raw_affiliation_strings":["Shizuoka University, Japan"],"affiliations":[{"raw_affiliation_string":"Shizuoka University, Japan","institution_ids":["https://openalex.org/I1298590031"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008020893","display_name":"Yugo Takeuchi","orcid":"https://orcid.org/0000-0002-5026-1837"},"institutions":[{"id":"https://openalex.org/I1298590031","display_name":"Shizuoka University","ror":"https://ror.org/01w6wtk13","country_code":"JP","type":"education","lineage":["https://openalex.org/I1298590031"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yugo Takeuchi","raw_affiliation_strings":["Shizuoka University, Japan"],"affiliations":[{"raw_affiliation_string":"Shizuoka University, Japan","institution_ids":["https://openalex.org/I1298590031"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5041250385"],"corresponding_institution_ids":["https://openalex.org/I1298590031"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18147,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"47","last_page":"55"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.9372000098228455,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.9372000098228455,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10315","display_name":"Decision-Making and Behavioral Economics","score":0.934499979019165,"subfield":{"id":"https://openalex.org/subfields/1800","display_name":"General Decision Sciences"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.639695405960083},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5203065872192383},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4796591103076935},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.43733978271484375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43582579493522644},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4229621887207031},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34066444635391235},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.1305447518825531}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.639695405960083},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5203065872192383},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4796591103076935},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.43733978271484375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43582579493522644},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4229621887207031},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34066444635391235},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.1305447518825531}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3472307.3484174","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3472307.3484174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Human-Agent Interaction","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W175549765","https://openalex.org/W1527544218","https://openalex.org/W1994335990","https://openalex.org/W2008073538","https://openalex.org/W2032737885","https://openalex.org/W2064604759","https://openalex.org/W2077110920","https://openalex.org/W2233096735","https://openalex.org/W2327414994","https://openalex.org/W2577366212","https://openalex.org/W4240537053","https://openalex.org/W4241412659"],"related_works":["https://openalex.org/W2372267530","https://openalex.org/W2969189870","https://openalex.org/W2965643117","https://openalex.org/W4303857162","https://openalex.org/W2407375987","https://openalex.org/W3049691116","https://openalex.org/W2505726097","https://openalex.org/W2010643158","https://openalex.org/W2106867672","https://openalex.org/W3081214562"],"abstract_inverted_index":{"In":[0,47,84,129],"the":[1,15,19,22,33,39,49,53,59,75,85,97,104,117,130,140,146,152,160,165,168,183,186,190,193,198,205,215,218,231,242],"field":[2],"of":[3,8,55,62,87,100,119,170,185,195,214,223,233,244,247],"social":[4],"psychology,":[5],"a":[6,28,93,113,126,134,211,238],"number":[7,169],"indebtedness":[9,16,37,63,78,103,187,207],"models":[10],"have":[11],"been":[12,45,66],"discussed.":[13,46],"However,":[14],"felt":[17,188],"by":[18,122,189],"recipient":[20,191],"for":[21,139,197,217,240],"aid":[23],"received":[24],"is":[25,70,92,137],"based":[26],"on":[27,108],"recipient\u2019s":[29,40],"subjective":[30],"evaluation,":[31],"and":[32,58,145,167,192,209],"extent":[34],"to":[35,72,80,95,125,142,150,162,164,181,228,230],"which":[36],"affects":[38],"subsequent":[41],"behavior":[42],"has":[43,64],"rarely":[44],"addition,":[48],"quantitative":[50,98,212],"relationship":[51],"between":[52],"amount":[54,61,118,194],"help":[56,120,219],"given":[57,121,159],"corresponding":[60],"not":[65],"clarified.":[67],"Therefore,":[68],"it":[69],"difficult":[71,138],"directly":[73],"apply":[74],"conventional":[76,206],"qualitative":[77],"model":[79,114,208],"human\u2013agent":[81],"interactions":[82],"(HAIs).":[83],"design":[86,232],"interpersonal":[88,234],"assistance":[89,106,199,235],"agents,":[90],"there":[91],"need":[94],"clarify":[96],"index":[99],"how":[101],"much":[102],"agents\u2019":[105],"imposes":[107],"users.":[109],"This":[110],"study":[111,225],"developed":[112],"that":[115,136],"predicts":[116],"an":[123],"agent":[124,147],"specific":[127],"recipient.":[128],"experiment,":[131],"we":[132],"imposed":[133],"task":[135],"participants":[141,156],"accomplish":[143],"independently,":[144],"assisted":[148],"them":[149],"reproduce":[151],"helping":[153],"scene.":[154],"The":[155,174,201,221],"were":[157,176],"then":[158],"opportunity":[161],"respond":[163],"agent,":[166],"responses":[171],"was":[172],"observed.":[173],"results":[175,202,222],"analyzed":[177],"using":[178],"Bayesian":[179],"statistics":[180],"estimate":[182],"magnitude":[184,243],"return":[196],"given.":[200,220],"generally":[203],"supported":[204],"provided":[210],"measure":[213],"reciprocation":[216],"this":[224],"are":[226],"expected":[227],"contribute":[229],"agents":[236],"as":[237],"criterion":[239],"considering":[241],"users\u2019":[245],"feelings":[246],"indebtedness.":[248]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}