{"id":"https://openalex.org/W4282937522","doi":"https://doi.org/10.48550/arxiv.2206.05357","title":"Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning","display_name":"Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning","publication_year":2022,"publication_date":"2022-06-10","ids":{"openalex":"https://openalex.org/W4282937522","doi":"https://doi.org/10.48550/arxiv.2206.05357"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2206.05357","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.05357","pdf_url":"https://arxiv.org/pdf/2206.05357","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":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2206.05357","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029262439","display_name":"Ruida Zhou","orcid":"https://orcid.org/0000-0002-8855-2031"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhou, Ruida","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100338076","display_name":"Tao Liu","orcid":"https://orcid.org/0009-0002-9261-6728"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Tao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053096993","display_name":"Dileep Kalathil","orcid":"https://orcid.org/0000-0001-7968-5185"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kalathil, Dileep","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047512433","display_name":"P. R. Kumar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kumar, P. R.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100675045","display_name":"Chao Tian","orcid":"https://orcid.org/0000-0001-8752-6141"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tian, Chao","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5029262439"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9965000152587891,"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":0.9965000152587891,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9409999847412109,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9347000122070312,"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/markov-decision-process","display_name":"Markov decision process","score":0.8477528691291809},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.809404730796814},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6906201839447021},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6781520843505859},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5645636320114136},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4488454759120941},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.3638027310371399},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.35451948642730713},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3330993354320526},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17611920833587646},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11800774931907654},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.10302209854125977},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08110669255256653}],"concepts":[{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.8477528691291809},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.809404730796814},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6906201839447021},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6781520843505859},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5645636320114136},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4488454759120941},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.3638027310371399},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.35451948642730713},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3330993354320526},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17611920833587646},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11800774931907654},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.10302209854125977},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08110669255256653},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2206.05357","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.05357","pdf_url":"https://arxiv.org/pdf/2206.05357","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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2206.05357","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2206.05357","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2206.05357","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.05357","pdf_url":"https://arxiv.org/pdf/2206.05357","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":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.699999988079071,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3096874164","https://openalex.org/W1985560493","https://openalex.org/W2937181779","https://openalex.org/W2386410636","https://openalex.org/W2357975469","https://openalex.org/W2145363145","https://openalex.org/W1626977535","https://openalex.org/W2341346307","https://openalex.org/W3168977894","https://openalex.org/W2182304831"],"abstract_inverted_index":{"We":[0,38],"study":[1],"policy":[2,61,96],"optimization":[3,62],"for":[4,64],"Markov":[5],"decision":[6],"processes":[7],"(MDPs)":[8],"with":[9,81],"multiple":[10],"reward":[11],"value":[12],"functions,":[13],"which":[14,48],"are":[15],"to":[16,21,93],"be":[17],"jointly":[18],"optimized":[19],"according":[20],"given":[22],"criteria":[23],"such":[24],"as":[25],"proportional":[26],"fairness":[27],"(smooth":[28],"concave":[29],"scalarization),":[30],"hard":[31],"constraints":[32],"(constrained":[33],"MDP),":[34],"and":[35,103],"max-min":[36],"trade-off.":[37],"propose":[39],"an":[40],"Anchor-changing":[41],"Regularized":[42],"Natural":[43],"Policy":[44],"Gradient":[45],"(ARNPG)":[46],"framework,":[47],"can":[49],"systematically":[50],"incorporate":[51],"ideas":[52],"from":[53],"well-performing":[54],"first-order":[55],"methods":[56],"into":[57],"the":[58,69,74,85],"design":[59],"of":[60],"algorithms":[63,71,87],"multi-objective":[65],"MDP":[66],"problems.":[67],"Theoretically,":[68],"designed":[70],"based":[72],"on":[73],"ARNPG":[75],"framework":[76],"achieve":[77],"$\\tilde{O}(1/T)$":[78],"global":[79],"convergence":[80],"exact":[82,101],"gradients.":[83],"Empirically,":[84],"ARNPG-guided":[86],"also":[88],"demonstrate":[89],"superior":[90],"performance":[91],"compared":[92],"some":[94],"existing":[95],"gradient-based":[97],"approaches":[98],"in":[99],"both":[100],"gradients":[102],"sample-based":[104],"scenarios.":[105]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2022-06-16T00:00:00"}
