{"id":"https://openalex.org/W4391889467","doi":"https://doi.org/10.1109/comsnets59351.2024.10427302","title":"Quantum-Enhanced Resilient Reinforcement Learning Using Causal Inference","display_name":"Quantum-Enhanced Resilient Reinforcement Learning Using Causal Inference","publication_year":2024,"publication_date":"2024-01-03","ids":{"openalex":"https://openalex.org/W4391889467","doi":"https://doi.org/10.1109/comsnets59351.2024.10427302"},"language":"en","primary_location":{"id":"doi:10.1109/comsnets59351.2024.10427302","is_oa":false,"landing_page_url":"https://doi.org/10.1109/comsnets59351.2024.10427302","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093836188","display_name":"Namasi G. Sankar","orcid":null},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]},{"id":"https://openalex.org/I181996519","display_name":"Indian Institute of Science Education and Research Pune","ror":"https://ror.org/028qa3n13","country_code":"IN","type":"education","lineage":["https://openalex.org/I181996519"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Namasi G. Sankar","raw_affiliation_strings":["Indian Institute of Science Education and Research,Pune,India","Indian Institute of Science Education and Research, Pune, India","TCS Research, Tata Consultancy Services, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Science Education and Research,Pune,India","institution_ids":["https://openalex.org/I181996519"]},{"raw_affiliation_string":"Indian Institute of Science Education and Research, Pune, India","institution_ids":["https://openalex.org/I181996519"]},{"raw_affiliation_string":"TCS Research, Tata Consultancy Services, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074061540","display_name":"Ankit Khandelwal","orcid":"https://orcid.org/0000-0003-0020-6546"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ankit Khandelwal","raw_affiliation_strings":["TCS Research, Tata Consultancy Services,India","TCS Research, Tata Consultancy Services, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, Tata Consultancy Services,India","institution_ids":["https://openalex.org/I55215948"]},{"raw_affiliation_string":"TCS Research, Tata Consultancy Services, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035666448","display_name":"M Girish Chandra","orcid":"https://orcid.org/0000-0002-1479-0504"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"M Girish Chandra","raw_affiliation_strings":["TCS Research, Tata Consultancy Services,India","TCS Research, Tata Consultancy Services, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, Tata Consultancy Services,India","institution_ids":["https://openalex.org/I55215948"]},{"raw_affiliation_string":"TCS Research, Tata Consultancy Services, India","institution_ids":["https://openalex.org/I55215948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5093836188"],"corresponding_institution_ids":["https://openalex.org/I181996519","https://openalex.org/I55215948"],"apc_list":null,"apc_paid":null,"fwci":0.7252,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.72702214,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1058","last_page":"1063"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10020","display_name":"Quantum Information and Cryptography","score":0.9121000170707703,"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/T10020","display_name":"Quantum Information and Cryptography","score":0.9121000170707703,"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":0.8153983354568481},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6633768081665039},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.570417582988739},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48593321442604065},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.4247291088104248},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35309529304504395},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10472247004508972}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8153983354568481},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6633768081665039},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.570417582988739},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48593321442604065},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.4247291088104248},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35309529304504395},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10472247004508972},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/comsnets59351.2024.10427302","is_oa":false,"landing_page_url":"https://doi.org/10.1109/comsnets59351.2024.10427302","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2156737235","https://openalex.org/W2746553466","https://openalex.org/W2754535787","https://openalex.org/W2769169032","https://openalex.org/W2781738013","https://openalex.org/W2908510526","https://openalex.org/W2914584698","https://openalex.org/W2954939433","https://openalex.org/W2990961515","https://openalex.org/W3045093737","https://openalex.org/W3098599423","https://openalex.org/W3100931082","https://openalex.org/W3104418005","https://openalex.org/W3124542169","https://openalex.org/W3141755656","https://openalex.org/W4285815497","https://openalex.org/W4289606390","https://openalex.org/W4295312788","https://openalex.org/W4298857966","https://openalex.org/W4302012993","https://openalex.org/W4312278356","https://openalex.org/W4312936103","https://openalex.org/W6605270721","https://openalex.org/W6685444567","https://openalex.org/W6766978945","https://openalex.org/W6838679854"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Deep":[0,81],"Reinforcement":[1],"Learning":[2,9],"(DRL)":[3],"is":[4,146,162],"a":[5,80],"sub-field":[6],"of":[7,61,153],"Machine":[8],"(ML)":[10],"that":[11,85,111],"combines":[12],"reinforcement":[13],"learning":[14,18,58],"(RL)":[15],"with":[16,88],"deep":[17],"techniques.":[19],"DRL":[20,32,62],"has":[21],"showcased":[22],"promising":[23],"results":[24],"in":[25,50,102,138],"gaming":[26],"environments":[27],"and":[28,59,118,129,161],"real-world":[29],"applications.":[30,52],"However,":[31],"agents":[33,63],"are":[34,66,133],"susceptible":[35],"to":[36,40],"faulty":[37],"observations":[38],"due":[39],"sudden":[41],"interference":[42,49],"like":[43],"blackouts,":[44],"frozen":[45],"observation,":[46],"or":[47],"adversarial":[48],"practical":[51],"These":[53],"scenarios":[54],"can":[55],"hamper":[56],"the":[57,74,107,112,151,154,165],"performance":[60,117],"if":[64],"they":[65],"not":[67],"resilient.":[68],"Drawing":[69],"inspiration":[70],"from":[71],"causal":[72],"inference,":[73],"Causal":[75],"In-ference":[76],"Q-Network":[77,82],"(CIQ)":[78],"explores":[79],"(DQN)":[83],"framework":[84],"undergoes":[86],"training":[87,94],"an":[89,99],"additional":[90],"task":[91],"focusing":[92],"on":[93],"for":[95,135,169],"observational":[96,122],"interference.":[97,123],"Through":[98],"evaluation":[100],"conducted":[101],"various":[103],"benchmark":[104],"DQN":[105],"environments,":[106],"experimental":[108],"findings":[109],"demonstrate":[110],"CIQ":[113,155],"method":[114],"exhibits":[115],"enhanced":[116],"greater":[119],"resilience":[120,137],"against":[121,164],"In":[124],"this":[125],"paper,":[126],"quantum":[127],"networks":[128,132,168],"hybrid":[130],"quantum-classical":[131],"tested":[134],"their":[136],"noisy":[139],"environments.":[140],"A":[141],"novel":[142],"Quantum-Enhanced":[143],"CIQ-Network":[144],"(QCIQ)":[145],"proposed":[147],"which":[148],"could":[149],"replicate":[150],"functioning":[152],"using":[156],"Variational":[157],"Quantum":[158],"Circuits":[159],"(VQCs)":[160],"benchmarked":[163],"corresponding":[166],"classical":[167],"its":[170],"performance.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}