{"id":"https://openalex.org/W4415055019","doi":"https://doi.org/10.48550/arxiv.2509.06094","title":"Teaching Precommitted Agents: Model-Free Policy Evaluation and Control in Quasi-Hyperbolic Discounted MDPs","display_name":"Teaching Precommitted Agents: Model-Free Policy Evaluation and Control in Quasi-Hyperbolic Discounted MDPs","publication_year":2025,"publication_date":"2025-09-07","ids":{"openalex":"https://openalex.org/W4415055019","doi":"https://doi.org/10.48550/arxiv.2509.06094"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2509.06094","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.06094","pdf_url":"https://arxiv.org/pdf/2509.06094","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2509.06094","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018071013","display_name":"S. R. Eshwar","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Eshwar, S. R.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5018071013"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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/T12288","display_name":"Optimization and Search Problems","score":0.4401000142097473,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12288","display_name":"Optimization and Search Problems","score":0.4401000142097473,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10603","display_name":"Smart Grid Energy Management","score":0.39079999923706055,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.36559998989105225,"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":0.6851999759674072},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6722999811172485},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.6003999710083008},{"id":"https://openalex.org/keywords/discounting","display_name":"Discounting","score":0.5533000230789185},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.5529000163078308},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.550599992275238},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5020999908447266}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6851999759674072},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6722999811172485},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6503000259399414},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.6003999710083008},{"id":"https://openalex.org/C6177178","wikidata":"https://www.wikidata.org/wiki/Q10998070","display_name":"Discounting","level":2,"score":0.5533000230789185},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.5529000163078308},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.550599992275238},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5020999908447266},{"id":"https://openalex.org/C127729010","wikidata":"https://www.wikidata.org/wiki/Q60165","display_name":"Dynamic inconsistency","level":2,"score":0.41749998927116394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3813999891281128},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3506999909877777},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.3409999907016754},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.32440000772476196},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2962999939918518},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2777999937534332},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.2745000123977661},{"id":"https://openalex.org/C178562925","wikidata":"https://www.wikidata.org/wiki/Q186412","display_name":"Time preference","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2509.06094","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.06094","pdf_url":"https://arxiv.org/pdf/2509.06094","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"doi:10.48550/arxiv.2509.06094","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.06094","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":"pmh:oai:arXiv.org:2509.06094","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.06094","pdf_url":"https://arxiv.org/pdf/2509.06094","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Time-inconsistent":[0],"preferences,":[1],"where":[2],"agents":[3,52],"favor":[4],"smaller-sooner":[5],"over":[6],"larger-later":[7],"rewards,":[8],"are":[9],"a":[10,22,80],"key":[11,45],"feature":[12],"of":[13,67],"human":[14],"and":[15,47,85,98],"animal":[16],"decision-making.":[17],"Quasi-Hyperbolic":[18],"(QH)":[19],"discounting":[20],"provides":[21],"simple":[23,81],"yet":[24],"powerful":[25],"model":[26],"for":[27,50,72,94,113],"this":[28,101],"behavior,":[29],"but":[30],"its":[31],"integration":[32],"into":[33],"the":[34,65,68,73,89],"reinforcement":[35],"learning":[36],"(RL)":[37],"framework":[38],"has":[39],"been":[40],"limited.":[41],"This":[42],"paper":[43],"addresses":[44],"theoretical":[46],"algorithmic":[48],"gaps":[49],"precommitted":[51],"with":[53,104],"QH":[54,115],"preferences.":[55],"We":[56],"make":[57],"two":[58],"primary":[59],"contributions:":[60],"(i)":[61],"we":[62,87],"formally":[63],"characterize":[64],"structure":[66],"optimal":[69],"policy,":[70],"proving":[71],"first":[74,90],"time":[75],"that":[76],"it":[77],"reduces":[78],"to":[79],"one-step":[82],"non-stationary":[83],"form;":[84],"(ii)":[86],"design":[88],"practical,":[91],"model-free":[92],"algorithms":[93],"both":[95,103],"policy":[96],"evaluation":[97],"Q-learning":[99],"in":[100,117],"setting,":[102],"provable":[105],"convergence":[106],"guarantees.":[107],"Our":[108],"results":[109],"provide":[110],"foundational":[111],"insights":[112],"incorporating":[114],"preferences":[116],"RL.":[118]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-11T00:00:00"}
