乐胖代购免代理版

{"id":"https://openalex.org/W4387839201","doi":"https://doi.org/10.48550/arxiv.2310.12934","title":"Generative Flow Networks as Entropy-Regularized RL","display_name":"Generative Flow Networks as Entropy-Regularized RL","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4387839201","doi":"https://doi.org/10.48550/arxiv.2310.12934"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2310.12934","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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2310.12934","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050920275","display_name":"Daniil Tiapkin","orcid":"https://orcid.org/0000-0002-8832-7926"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tiapkin, Daniil","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091716956","display_name":"\u041d. \u0424. \u041c\u043e\u0440\u043e\u0437\u043e\u0432","orcid":"https://orcid.org/0000-0003-3890-522X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Morozov, Nikita","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010477635","display_name":"Alexey Naumov","orcid":"https://orcid.org/0000-0002-7536-4576"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Naumov, Alexey","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101595563","display_name":"Dmitry Vetrov","orcid":"https://orcid.org/0000-0001-6863-9028"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vetrov, Dmitry","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":68},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9928,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9928,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9151,"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":0.574803},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.42483816}],"concepts":[{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.78303343},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.73465157},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6966744},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6194636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5645721},{"id":"https://openalex.org/C2775922551","wikidata":"https://www.wikidata.org/wiki/Q7135033","display_name":"Parallels","level":2,"score":0.50850904},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5021131},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.44135556},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4384224},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.42483816},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2310.12934","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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.12934","pdf_url":"http://arxiv.org/pdf/2310.12934","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2310.12934","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2310.12934","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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4387506531","https://openalex.org/W4380551139","https://openalex.org/W4365211920","https://openalex.org/W4317695495","https://openalex.org/W4299831724","https://openalex.org/W4287117424","https://openalex.org/W4238433571","https://openalex.org/W3174044702","https://openalex.org/W3014948380","https://openalex.org/W2967848559"],"abstract_inverted_index":{"The":[0],"recently":[1],"proposed":[2],"generative":[3,66,141],"flow":[4,67,142],"networks":[5],"(GFlowNets)":[6],"are":[7],"a":[8,12,23,27,55,65,79,130],"method":[9],"of":[10,29,36,63,91,140],"training":[11,102,125],"policy":[13],"to":[14,22,54,100,109],"sample":[15],"compositional":[16],"discrete":[17],"objects":[18],"with":[19,41,78],"probabilities":[20],"proportional":[21],"given":[24],"reward":[25,81],"via":[26],"sequence":[28],"actions.":[30],"GFlowNets":[31,53],"exploit":[32],"the":[33,37,48,61,88,138],"sequential":[34],"nature":[35],"problem,":[38],"drawing":[39],"parallels":[40],"reinforcement":[42],"learning":[43,64],"(RL).":[44],"Our":[45],"work":[46],"extends":[47],"connection":[49],"between":[50],"RL":[51,76,98,117,135],"and":[52,82],"general":[56],"case.":[57],"We":[58],"demonstrate":[59],"how":[60],"task":[62],"network":[68],"can":[69,119],"be":[70,120],"efficiently":[71],"redefined":[72],"as":[73],"an":[74],"entropy-regularized":[75],"problem":[77],"specific":[80],"regularizer":[83],"structure.":[84],"Furthermore,":[85],"we":[86,113],"illustrate":[87],"practical":[89],"efficiency":[90],"this":[92],"reformulation":[93],"by":[94],"applying":[95],"standard":[96],"soft":[97],"algorithms":[99],"GFlowNet":[101,124],"across":[103],"several":[104],"probabilistic":[105],"modeling":[106],"tasks.":[107],"Contrary":[108],"previously":[110],"reported":[111],"results,":[112],"show":[114],"that":[115],"entropic":[116],"approaches":[118],"competitive":[121],"against":[122],"established":[123],"methods.":[126],"This":[127],"perspective":[128],"opens":[129],"direct":[131],"path":[132],"for":[133],"integrating":[134],"principles":[136],"into":[137],"realm":[139],"networks.":[143]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4387839201","counts_by_year":[],"updated_date":"2024-12-05T08:18:42.271092","created_date":"2023-10-21"}