{"id":"https://openalex.org/W7220916010","doi":"https://doi.org/10.3390/info17111132","title":"Reinforcement Learning in Recommender Systems for Personalized Financial Decision Support: A Systematic Mapping Study","display_name":"Reinforcement Learning in Recommender Systems for Personalized Financial Decision Support: A Systematic Mapping Study","publication_year":2026,"publication_date":"2026-11-11","ids":{"openalex":"https://openalex.org/W7220916010","doi":"https://doi.org/10.3390/info17111132"},"language":"en","primary_location":{"id":"doi:10.3390/info17111132","doi":"https://doi.org/10.3390/info17111132","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info17111132","pdf_url":null,"source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-40","russia-white-list-2","vabb-shw"],"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":"Information","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/info17111132","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5157961268","display_name":"Mathias Busubiri Mutembete","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mathias Busubiri Mutembete","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002216699","display_name":"Simon Nyaga Mwendia","orcid":"https://orcid.org/0000-0003-3553-2501","observed_orcids":["https://orcid.org/0000-0003-3553-2501"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Simon Nyaga Mwendia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5052375916","display_name":"Edwin Juma Omol","orcid":"https://orcid.org/0009-0009-7375-005X","observed_orcids":["https://orcid.org/0009-0009-7375-005X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Edwin Juma Omol","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1600,"currency":"CHF","value_usd":1930},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1930},"fwci":0.0,"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":null,"biblio":{"volume":"17","issue":"11","first_page":"1132","last_page":"1132"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9829000234603882,"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"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9829000234603882,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.012299999594688416,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.00139999995008111,"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":0.972000002861023},{"id":"https://openalex.org/keywords/recommender-systems","display_name":"recommender systems","score":0.9940000176429749},{"id":"https://openalex.org/keywords/financial-recommendations","display_name":"financial recommendations","score":0.5989999771118164},{"id":"https://openalex.org/keywords/multi-armed-bandits","display_name":"multi-armed bandits","score":0.8500000238418579},{"id":"https://openalex.org/keywords/contextual-bandits","display_name":"contextual bandits","score":0.9959999918937683},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.9369999766349792},{"id":"https://openalex.org/keywords/actor-critic","display_name":"actor-critic","score":0.8109999895095825},{"id":"https://openalex.org/keywords/policy-optimization","display_name":"policy optimization","score":0.6830000281333923},{"id":"https://openalex.org/keywords/reward-function-design","display_name":"reward function design","score":0.7910000085830688},{"id":"https://openalex.org/keywords/preference-elicitation","display_name":"preference elicitation","score":0.7459999918937683},{"id":"https://openalex.org/keywords/longitudinal-validation","display_name":"longitudinal validation","score":0.5220000147819519},{"id":"https://openalex.org/keywords/assessment-practices","display_name":"assessment practices","score":0.48500001430511475}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8227999806404114},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7710999846458435},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7601000070571899},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.510699987411499},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.5077000260353088},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49880000948905945},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.48590001463890076},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3873000144958496},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3644999861717224},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.34630000591278076},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C2777868144","wikidata":"https://www.wikidata.org/wiki/Q7239817","display_name":"Preference elicitation","level":3,"score":0.3246999979019165},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info17111132","doi":"https://doi.org/10.3390/info17111132","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info17111132","pdf_url":null,"source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-40","russia-white-list-2","vabb-shw"],"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":"Information","raw_type":"journal-article"},{"id":"doi:10.20944/preprints202610.0315.v1","doi":"https://doi.org/10.20944/preprints202610.0315.v1","is_oa":true,"landing_page_url":"https://doi.org/10.20944/preprints202610.0315.v1","pdf_url":null,"source":{"id":"https://openalex.org/S6309402219","display_name":"Preprints.org","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.3390/info17111132","doi":"https://doi.org/10.3390/info17111132","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info17111132","pdf_url":null,"source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-40","russia-white-list-2","vabb-shw"],"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":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[{"display_name":"Systematic Review","id":"https://openalex.org/study-designs/systematic-review"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7171616196","https://openalex.org/W4404431993","https://openalex.org/W2905775940","https://openalex.org/W7144010396","https://openalex.org/W7160431610","https://openalex.org/W7213667048","https://openalex.org/W2575337496","https://openalex.org/W4417297095","https://openalex.org/W4379527413","https://openalex.org/W7084123063"],"abstract_inverted_index":{"Reinforcement":[0],"learning":[1],"(RL)":[2],"and":[3,13,31,56,69,87,115,121,128,131,140,149,165,175,200,224,234,242,251],"bandit-based":[4],"methods":[5,102,117,126],"enable":[6],"recommender":[7,45],"systems":[8,46],"to":[9,11,80,180,210],"adapt":[10],"user":[12,218],"environmental":[14],"feedback,":[15],"offering":[16],"opportunities":[17],"for":[18,247],"personalized":[19,198,249],"financial":[20,183,215],"decision":[21,29,54,216,253],"support.":[22,254],"However,":[23,168],"evidence":[24,176],"concerning":[25],"their":[26],"methodological":[27,232],"integration,":[28],"formulation,":[30,55],"evaluation":[32,57,244],"remains":[33],"fragmented":[34],"across":[35,47],"application":[36],"domains.":[37],"This":[38,227],"systematic":[39,60],"mapping":[40,233],"study":[41,228],"examines":[42],"empirical":[43,99],"RL-enabled":[44],"four":[48],"dimensions:":[49],"RL":[50,112,133,212],"approach,":[51],"integration":[52],"role,":[53],"practices.":[58],"A":[59],"search":[61,123],"of":[62,94,197],"Scopus,":[63],"ACM":[64],"Digital":[65],"Library,":[66],"ScienceDirect,":[67],"SpringerLink,":[68],"IEEE":[70],"Xplore":[71],"identified":[72],"7531":[73],"records":[74],"covering":[75],"peer-reviewed":[76],"publications":[77],"from":[78],"2015":[79],"2025.":[81],"Following":[82],"deduplication,":[83],"screening,":[84],"eligibility":[85],"assessment,":[86],"quality":[88],"appraisal,":[89],"50":[90],"studies":[91,189],"were":[92,103,173],"retained,":[93],"which":[95],"28":[96],"underwent":[97],"focused":[98],"mapping.":[100],"Bandit-based":[101],"the":[104,208],"most":[105],"prevalent":[106],"approaches":[107],"(39.3%),":[108],"followed":[109],"by":[110],"value-based":[111,130],"(32.1%),":[113],"policy-gradient":[114],"policy-optimization":[116,132],"(14.3%),":[118],"model-based":[119],"planning":[120],"tree":[122],"(7.1%),":[124],"actor\u2013critic":[125],"(3.6%),":[127],"mixed":[129],"(3.6%).":[134],"RL-related":[135],"mechanisms":[136,213],"supported":[137],"direct":[138,169],"recommendation":[139,159,171],"policy":[141],"optimization,":[142],"recommender-strategy":[143],"selection,":[144],"representation":[145],"or":[146,152,192],"model":[147],"adaptation,":[148,241],"preference":[150],"elicitation":[151],"planning.":[153],"Reward":[154],"formulations":[155],"encompassed":[156],"behavioral":[157],"responses,":[158],"utility,":[160],"economic":[161],"objectives,":[162],"operational":[163],"costs,":[164],"feedback-derived":[166],"preferences.":[167],"financial-product":[170],"applications":[172],"limited,":[174],"linking":[177],"adaptive-learning":[178],"performance":[179],"sustained":[181],"user-level":[182],"outcomes":[184,202],"remained":[185],"insufficient.":[186],"Although":[187],"some":[188],"incorporated":[190],"online":[191],"human-participant":[193],"evaluation,":[194],"longitudinal":[195,243],"validation":[196],"savings":[199,250],"investment":[201,252],"was":[203],"limited.":[204],"The":[205],"findings":[206],"emphasize":[207],"need":[209],"align":[211],"with":[214],"contexts,":[217],"representations,":[219],"reward":[220,238],"functions,":[221],"feedback":[222],"structures,":[223],"suitability":[225],"constraints.":[226],"provides":[229],"a":[230],"structured":[231],"identifies":[235],"financially":[236],"meaningful":[237],"design,":[239],"constraint-aware":[240],"as":[245],"priorities":[246],"advancing":[248]},"counts_by_year":[],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2026-10-09T00:00:00"}
