{"id":"https://openalex.org/W3008163217","doi":"https://doi.org/10.29007/7jmg","title":"Deep Reinforcement Learning for Synthesizing Functions in Higher-Order Logic","display_name":"Deep Reinforcement Learning for Synthesizing Functions in Higher-Order Logic","publication_year":2020,"publication_date":"2020-05-27","ids":{"openalex":"https://openalex.org/W3008163217","doi":"https://doi.org/10.29007/7jmg","mag":"3008163217"},"language":"en","primary_location":{"id":"doi:10.29007/7jmg","is_oa":true,"landing_page_url":"https://doi.org/10.29007/7jmg","pdf_url":"https://easychair.org/publications/open/Tctp","source":{"id":"https://openalex.org/S4220651395","display_name":"EPiC series in computing","issn_l":"2398-7340","issn":["2398-7340"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPiC Series in Computing","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://easychair.org/publications/open/Tctp","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048490198","display_name":"Thibault Gauthier","orcid":"https://orcid.org/0000-0002-7348-0602"},"institutions":[{"id":"https://openalex.org/I44504214","display_name":"Czech Technical University in Prague","ror":"https://ror.org/03kqpb082","country_code":"CZ","type":"education","lineage":["https://openalex.org/I44504214"]}],"countries":["CZ"],"is_corresponding":true,"raw_author_name":"Thibault Gauthier","raw_affiliation_strings":["Czech Technical University in Prague, Prague, Czech Republic","Czech Technical University in Prague, Prague, Czechia"],"affiliations":[{"raw_affiliation_string":"Czech Technical University in Prague, Prague, Czech Republic","institution_ids":["https://openalex.org/I44504214"]},{"raw_affiliation_string":"Czech Technical University in Prague, Prague, Czechia","institution_ids":["https://openalex.org/I44504214"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5048490198"],"corresponding_institution_ids":["https://openalex.org/I44504214"],"apc_list":null,"apc_paid":null,"fwci":0.2743,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.62291937,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9907000064849854,"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"}},"topics":[{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9907000064849854,"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/T10260","display_name":"Software Engineering Research","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10126","display_name":"Logic, programming, and type systems","score":0.9804999828338623,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7892433404922485},{"id":"https://openalex.org/keywords/combinatory-logic","display_name":"Combinatory logic","score":0.7709875106811523},{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.7632495164871216},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7248713970184326},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5458805561065674},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.517853319644928},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.51686030626297},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4444357454776764},{"id":"https://openalex.org/keywords/tree-structure","display_name":"Tree structure","score":0.42922189831733704},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.41099661588668823},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.338026762008667},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2829355001449585},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.22817549109458923},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16785216331481934},{"id":"https://openalex.org/keywords/binary-tree","display_name":"Binary tree","score":0.14013075828552246},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.11432641744613647}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7892433404922485},{"id":"https://openalex.org/C79678938","wikidata":"https://www.wikidata.org/wiki/Q1481571","display_name":"Combinatory logic","level":2,"score":0.7709875106811523},{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.7632495164871216},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7248713970184326},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5458805561065674},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.517853319644928},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.51686030626297},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4444357454776764},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.42922189831733704},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.41099661588668823},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.338026762008667},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2829355001449585},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.22817549109458923},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16785216331481934},{"id":"https://openalex.org/C197855036","wikidata":"https://www.wikidata.org/wiki/Q380172","display_name":"Binary tree","level":2,"score":0.14013075828552246},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.11432641744613647},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.29007/7jmg","is_oa":true,"landing_page_url":"https://doi.org/10.29007/7jmg","pdf_url":"https://easychair.org/publications/open/Tctp","source":{"id":"https://openalex.org/S4220651395","display_name":"EPiC series in computing","issn_l":"2398-7340","issn":["2398-7340"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPiC Series in Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1910.11797","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.11797","pdf_url":"https://arxiv.org/pdf/1910.11797","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3008163217","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1910.11797.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1910.11797","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1910.11797","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.29007/7jmg","is_oa":true,"landing_page_url":"https://doi.org/10.29007/7jmg","pdf_url":"https://easychair.org/publications/open/Tctp","source":{"id":"https://openalex.org/S4220651395","display_name":"EPiC series in computing","issn_l":"2398-7340","issn":["2398-7340"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPiC Series in Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3008163217.pdf","grobid_xml":"https://content.openalex.org/works/W3008163217.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W1570380","https://openalex.org/W1781094","https://openalex.org/W123460044","https://openalex.org/W139596442","https://openalex.org/W159082583","https://openalex.org/W161513061","https://openalex.org/W219446931","https://openalex.org/W1481397690","https://openalex.org/W1507441114","https://openalex.org/W1515851193","https://openalex.org/W1573992413","https://openalex.org/W1595209293","https://openalex.org/W1780472831","https://openalex.org/W1789208025","https://openalex.org/W1943070836","https://openalex.org/W1985445827","https://openalex.org/W2002963758","https://openalex.org/W2005941052","https://openalex.org/W2007052128","https://openalex.org/W2072566913","https://openalex.org/W2077778948","https://openalex.org/W2096478770","https://openalex.org/W2119822741","https://openalex.org/W2126209209","https://openalex.org/W2126316555","https://openalex.org/W2251246155","https://openalex.org/W2262606152","https://openalex.org/W2290523257","https://openalex.org/W2295598076","https://openalex.org/W2581202535","https://openalex.org/W2766447205","https://openalex.org/W2786776430","https://openalex.org/W2795795481","https://openalex.org/W2801769268","https://openalex.org/W2804320211","https://openalex.org/W2804556168","https://openalex.org/W2907302928","https://openalex.org/W2914816563","https://openalex.org/W2932237430","https://openalex.org/W2962765587","https://openalex.org/W2963147113","https://openalex.org/W2964047362","https://openalex.org/W2969710508","https://openalex.org/W2990130865","https://openalex.org/W3099066793","https://openalex.org/W3102476541","https://openalex.org/W3105002484","https://openalex.org/W3106483625","https://openalex.org/W3139956803","https://openalex.org/W6679121739"],"related_works":["https://openalex.org/W3031858386","https://openalex.org/W2981907580","https://openalex.org/W2805447150","https://openalex.org/W1503527899","https://openalex.org/W1552228685","https://openalex.org/W2788411903","https://openalex.org/W1933411530","https://openalex.org/W1894395204","https://openalex.org/W1967346767","https://openalex.org/W1599090857","https://openalex.org/W1564663916","https://openalex.org/W3183732142","https://openalex.org/W2062315995","https://openalex.org/W3085238060","https://openalex.org/W2607462057","https://openalex.org/W2903639586","https://openalex.org/W2338592249","https://openalex.org/W3043557120","https://openalex.org/W3044725263","https://openalex.org/W2918963915"],"abstract_inverted_index":{"The":[0],"paper":[1],"describes":[2],"a":[3,61,66,72,81,117,139],"deep":[4],"reinforcement":[5],"learning":[6,11,23,41],"framework":[7],"based":[8],"on":[9,106,122],"self-supervised":[10],"within":[12],"the":[13,21,26,32,44,88,97,152],"proof":[14],"assistant":[15],"HOL4.":[16],"A":[17],"close":[18],"interaction":[19],"between":[20],"machine":[22,40],"modules":[24],"and":[25,43,91,108,113],"HOL4":[27,48],"library":[28],"is":[29,58,63],"achieved":[30],"by":[31,80,148],"choice":[33],"of":[34,47,54,120,135,145,151],"tree":[35,52],"neural":[36],"networks":[37],"(TNNs)":[38],"as":[39,65],"models":[42],"internal":[45],"use":[46],"terms":[49],"to":[50,86],"represent":[51],"structures":[53],"TNNs.":[55],"Recursive":[56],"improvement":[57],"possible":[59],"when":[60],"task":[62],"expressed":[64],"search":[67,89],"problem.":[68],"In":[69],"this":[70],"case,":[71],"Monte":[73],"Carlo":[74],"Tree":[75],"Search":[76],"(MCTS)":[77],"algorithm":[78],"guided":[79,143],"TNN":[82],"can":[83],"be":[84],"used":[85],"explore":[87],"space":[90],"produce":[92],"better":[93],"examples":[94],"for":[95,141],"training":[96],"next":[98],"TNN.":[99],"As":[100],"an":[101],"illustration,":[102],"term":[103],"synthesis":[104,124,144],"tasks":[105],"combinators":[107],"Diophantine":[109,146],"equations":[110,147],"are":[111],"specified":[112],"learned.":[114],"We":[115,137],"achieve":[116],"success":[118],"rate":[119],"65%":[121],"combinator":[123],"problems":[125],"outperforming":[126],"state-of-the-art":[127],"ATPs":[128],"run":[129],"with":[130],"their":[131],"best":[132],"general":[133],"set":[134,138],"strategies.":[136],"precedent":[140],"statistically":[142],"solving":[149],"78.5%":[150],"generated":[153],"test":[154],"problems.":[155]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-21T08:13:44.787528","created_date":"2022-07-28T00:00:00"}
