{"id":"https://openalex.org/W4306377223","doi":"https://doi.org/10.3390/e24101469","title":"A Formal Framework for Knowledge Acquisition: Going beyond Machine Learning","display_name":"A Formal Framework for Knowledge Acquisition: Going beyond Machine Learning","publication_year":2022,"publication_date":"2022-10-14","ids":{"openalex":"https://openalex.org/W4306377223","doi":"https://doi.org/10.3390/e24101469","pmid":"https://pubmed.ncbi.nlm.nih.gov/37420489"},"language":"en","primary_location":{"id":"doi:10.3390/e24101469","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24101469","pdf_url":"https://www.mdpi.com/1099-4300/24/10/1469/pdf?version=1666598744","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/24/10/1469/pdf?version=1666598744","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066828213","display_name":"Ola H\u00f6ssjer","orcid":"https://orcid.org/0000-0003-2767-8818"},"institutions":[{"id":"https://openalex.org/I161593684","display_name":"Stockholm University","ror":"https://ror.org/05f0yaq80","country_code":"SE","type":"education","lineage":["https://openalex.org/I161593684"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Ola H\u00f6ssjer","raw_affiliation_strings":["Department of Mathematics, Stockholm University, SE-106 91 Stockholm, Sweden"],"raw_orcid":"https://orcid.org/0000-0003-2767-8818","affiliations":[{"raw_affiliation_string":"Department of Mathematics, Stockholm University, SE-106 91 Stockholm, Sweden","institution_ids":["https://openalex.org/I161593684"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066515085","display_name":"Daniel Andr\u00e9s D\u00edaz\u2013Pach\u00f3n","orcid":"https://orcid.org/0000-0001-6281-1720"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Daniel Andr\u00e9s D\u00edaz-Pach\u00f3n","raw_affiliation_strings":["Division of Biostatistics, University of Miami, Miami, FL 33136, USA"],"raw_orcid":"https://orcid.org/0000-0001-6281-1720","affiliations":[{"raw_affiliation_string":"Division of Biostatistics, University of Miami, Miami, FL 33136, USA","institution_ids":["https://openalex.org/I145608581"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060541476","display_name":"J. Sunil Rao","orcid":"https://orcid.org/0000-0002-6450-3200"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Sunil Rao","raw_affiliation_strings":["Division of Biostatistics, University of Miami, Miami, FL 33136, USA"],"raw_orcid":"https://orcid.org/0000-0002-6450-3200","affiliations":[{"raw_affiliation_string":"Division of Biostatistics, University of Miami, Miami, FL 33136, USA","institution_ids":["https://openalex.org/I145608581"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5066515085"],"corresponding_institution_ids":["https://openalex.org/I145608581"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.9133,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77798467,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"24","issue":"10","first_page":"1469","last_page":"1469"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12002","display_name":"Computability, Logic, AI Algorithms","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12002","display_name":"Computability, Logic, AI Algorithms","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10906","display_name":"AI-based Problem Solving and Planning","score":0.9726999998092651,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11801","display_name":"Reservoir Engineering and Simulation Methods","score":0.9613000154495239,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6121572852134705},{"id":"https://openalex.org/keywords/knowledge-acquisition","display_name":"Knowledge acquisition","score":0.5822272896766663},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42021268606185913},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3946654200553894},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.33886635303497314}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6121572852134705},{"id":"https://openalex.org/C2777220311","wikidata":"https://www.wikidata.org/wiki/Q6423340","display_name":"Knowledge acquisition","level":2,"score":0.5822272896766663},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42021268606185913},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3946654200553894},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.33886635303497314}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e24101469","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24101469","pdf_url":"https://www.mdpi.com/1099-4300/24/10/1469/pdf?version=1666598744","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:37420489","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37420489","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:07dc24829558486596adbd6e7d0493f5","is_oa":true,"landing_page_url":"https://doaj.org/article/07dc24829558486596adbd6e7d0493f5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 24, Iss 10, p 1469 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/24/10/1469/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e24101469","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 24; Issue 10; Pages: 1469","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9601974","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9601974","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e24101469","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24101469","pdf_url":"https://www.mdpi.com/1099-4300/24/10/1469/pdf?version=1666598744","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309840","display_name":"Baylor University","ror":"https://ror.org/005781934"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4306377223.pdf","grobid_xml":"https://content.openalex.org/works/W4306377223.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W121824094","https://openalex.org/W1535258871","https://openalex.org/W1681695349","https://openalex.org/W1966129247","https://openalex.org/W1987949663","https://openalex.org/W2004060143","https://openalex.org/W2009708711","https://openalex.org/W2015040676","https://openalex.org/W2017170340","https://openalex.org/W2021553591","https://openalex.org/W2027608755","https://openalex.org/W2029205241","https://openalex.org/W2057720927","https://openalex.org/W2063268774","https://openalex.org/W2069138412","https://openalex.org/W2082080810","https://openalex.org/W2099939838","https://openalex.org/W2110575115","https://openalex.org/W2112090702","https://openalex.org/W2125474556","https://openalex.org/W2143891888","https://openalex.org/W2157965697","https://openalex.org/W2169605107","https://openalex.org/W2604217321","https://openalex.org/W2607455562","https://openalex.org/W2724168156","https://openalex.org/W2736618479","https://openalex.org/W2887693548","https://openalex.org/W2903720301","https://openalex.org/W2903891271","https://openalex.org/W2951307730","https://openalex.org/W2964012073","https://openalex.org/W3006719132","https://openalex.org/W3020915226","https://openalex.org/W3033459730","https://openalex.org/W3087788559","https://openalex.org/W3124062519","https://openalex.org/W3153095692","https://openalex.org/W3159836698","https://openalex.org/W3188343569","https://openalex.org/W3198921626","https://openalex.org/W4205801708","https://openalex.org/W4214717370","https://openalex.org/W4214854436","https://openalex.org/W4249128886","https://openalex.org/W4249186015","https://openalex.org/W4288058252","https://openalex.org/W4296991981","https://openalex.org/W4299413118","https://openalex.org/W4299551239","https://openalex.org/W4309673510","https://openalex.org/W4319590843","https://openalex.org/W6621483976","https://openalex.org/W6636237765","https://openalex.org/W6675535206","https://openalex.org/W6740078403"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Philosophers":[0],"frequently":[1],"define":[2,18],"knowledge":[3,26,153,168,228],"as":[4,144],"justified,":[5],"true":[6,23,48,85,160],"belief.":[7],"We":[8],"built":[9],"a":[10,58,69,84,102,124,134,145,150,159,171,182],"mathematical":[11],"framework":[12,125,164],"that":[13,111,129],"makes":[14,138],"it":[15,139],"possible":[16,140],"to":[17,131,141,181,217],"learning":[19,112,143,166,225],"(increasing":[20],"number":[21],"of":[22,27,38,47,54,63,65,81,99,126,133,158,165,199,207,220],"beliefs)":[24],"and":[25,68,118,167,175,187,203,209],"an":[28],"agent":[29,67],"in":[30,36,83,89,101,119,231],"precise":[31],"ways,":[32],"by":[33,52],"phrasing":[34],"belief":[35,49,64,82,100],"terms":[37],"epistemic":[39],"probabilities,":[40],"defined":[41],"from":[42],"Bayes'":[43],"rule.":[44],"The":[45,193],"degree":[46,62],"is":[50,170,195,230],"quantified":[51],"means":[53],"active":[55],"information":[56,186],"I+:":[57],"comparison":[59,90],"between":[60,173],"the":[61,66,78,92,97,115],"completely":[70],"ignorant":[71,93],"person.":[72],"Learning":[73],"has":[74,87,105],"occurred":[75],"when":[76],"either":[77],"agent's":[79],"strength":[80,98],"proposition":[86,104],"increased":[88],"with":[91],"person":[94],"(I+>0),":[95],"or":[96],"false":[103],"decreased":[106],"(I+<0).":[107],"Knowledge":[108],"additionally":[109,155],"requires":[110,156],"occurs":[113],"for":[114,148],"right":[116],"reason,":[117],"this":[120],"context":[121],"we":[122],"introduce":[123],"parallel":[127],"worlds":[128],"correspond":[130],"parameters":[132],"statistical":[135],"model.":[136],"This":[137],"interpret":[142],"hypothesis":[146],"test":[147],"such":[149],"model,":[151],"whereas":[152],"acquisition":[154,169,229],"estimation":[157],"world":[161],"parameter.":[162],"Our":[163],"hybrid":[172],"frequentism":[174],"Bayesianism.":[176],"It":[177,212],"can":[178,213],"be":[179,215],"generalized":[180],"sequential":[183],"setting,":[184],"where":[185,223],"data":[188],"are":[189],"updated":[190],"over":[191],"time.":[192],"theory":[194],"illustrated":[196],"using":[197],"examples":[198],"coin":[200],"tossing,":[201],"historical":[202],"future":[204],"events,":[205],"replication":[206],"studies,":[208],"causal":[210],"inference.":[211],"also":[214],"used":[216],"pinpoint":[218],"shortcomings":[219],"machine":[221],"learning,":[222],"typically":[224],"rather":[226],"than":[227],"focus.":[232]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}