{"id":"https://openalex.org/W3047967462","doi":"https://doi.org/10.1109/aim43001.2020.9158839","title":"Reinforcement Learning with Imitation for Cavity Filter Tuning","display_name":"Reinforcement Learning with Imitation for Cavity Filter Tuning","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3047967462","doi":"https://doi.org/10.1109/aim43001.2020.9158839","mag":"3047967462"},"language":"en","primary_location":{"id":"doi:10.1109/aim43001.2020.9158839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aim43001.2020.9158839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)","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/A5054353086","display_name":"Simon Lindstah","orcid":null},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Simon Lindstah","raw_affiliation_strings":["Ericsson Research, Stock-holm, Sweden"],"affiliations":[{"raw_affiliation_string":"Ericsson Research, Stock-holm, Sweden","institution_ids":["https://openalex.org/I1306339040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085322891","display_name":"Xiaoyu Lan","orcid":"https://orcid.org/0009-0005-1324-8085"},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Xiaoyu Lan","raw_affiliation_strings":["Ericsson Research, Stock-holm, Sweden"],"affiliations":[{"raw_affiliation_string":"Ericsson Research, Stock-holm, Sweden","institution_ids":["https://openalex.org/I1306339040"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5054353086"],"corresponding_institution_ids":["https://openalex.org/I1306339040"],"apc_list":null,"apc_paid":null,"fwci":0.2651,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.62872325,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1335","last_page":"1340"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.9886999726295471,"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/T12031","display_name":"Speech and dialogue systems","score":0.9886999726295471,"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/T10860","display_name":"Speech and Audio Processing","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12784","display_name":"Modular Robots and Swarm Intelligence","score":0.963699996471405,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8273718953132629},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.7446963787078857},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7386808395385742},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5686766505241394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5343182682991028},{"id":"https://openalex.org/keywords/imitation","display_name":"Imitation","score":0.5061160922050476},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4791752099990845},{"id":"https://openalex.org/keywords/fine-tuning","display_name":"Fine-tuning","score":0.47037142515182495},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.4284040927886963},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.42613688111305237},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3933559060096741},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1643843948841095},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13632535934448242},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.11696738004684448}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8273718953132629},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.7446963787078857},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7386808395385742},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5686766505241394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5343182682991028},{"id":"https://openalex.org/C126388530","wikidata":"https://www.wikidata.org/wiki/Q1131737","display_name":"Imitation","level":2,"score":0.5061160922050476},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4791752099990845},{"id":"https://openalex.org/C157524613","wikidata":"https://www.wikidata.org/wiki/Q2828883","display_name":"Fine-tuning","level":2,"score":0.47037142515182495},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.4284040927886963},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.42613688111305237},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3933559060096741},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1643843948841095},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13632535934448242},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.11696738004684448},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aim43001.2020.9158839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aim43001.2020.9158839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W112666333","https://openalex.org/W1757796397","https://openalex.org/W2020018978","https://openalex.org/W2149984847","https://openalex.org/W2289573517","https://openalex.org/W2524982318","https://openalex.org/W2575705757","https://openalex.org/W2766447205","https://openalex.org/W2804930149","https://openalex.org/W2909020706","https://openalex.org/W2962787969","https://openalex.org/W2963864421","https://openalex.org/W4243639737","https://openalex.org/W4297664295","https://openalex.org/W4298857966","https://openalex.org/W6604566608","https://openalex.org/W6637967152","https://openalex.org/W6684921986","https://openalex.org/W6745620495","https://openalex.org/W6752165109"],"related_works":["https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2778153218","https://openalex.org/W1531601525","https://openalex.org/W4281847915","https://openalex.org/W3000635674","https://openalex.org/W3007554156","https://openalex.org/W2995653869"],"abstract_inverted_index":{"Cavity":[0,135],"filters":[1],"are":[2,70],"vital":[3],"components":[4],"of":[5],"radio":[6],"base":[7],"stations":[8],"and":[9,27,63,72,81,113],"networks.":[10],"After":[11],"production,":[12],"they":[13],"need":[14],"tuning,":[15],"which":[16],"has":[17,122],"proven":[18],"to":[19,24,31,35,44,65],"be":[20],"a":[21,76,99,123],"difficult":[22],"process":[23,38],"do":[25],"manually":[26],"even":[28],"more":[29],"so":[30],"automate.":[32],"Previous":[33],"attempts":[34],"automate":[36],"this":[37,56,118,120],"with":[39,103],"Reinforcement":[40,132],"Learning":[41,94,133],"have":[42],"failed":[43],"reach":[45],"consistent":[46],"performance":[47],"on":[48,131],"anything":[49],"but":[50],"the":[51,83],"simplest":[52],"filter":[53,101,136],"models.":[54],"In":[55,88],"paper,":[57],"we":[58],"build":[59],"upon":[60],"these":[61],"results":[62,130],"aim":[64],"improve":[66],"them.":[67],"Multiple":[68],"methods":[69],"tested":[71],"evaluated,":[73],"including":[74],"introducing":[75],"pre-processing":[77],"step,":[78],"tuning":[79,105],"hyperparameters":[80],"dividing":[82],"problem":[84],"into":[85],"multiple":[86],"sub-tasks.":[87],"particular,":[89],"by":[90],"using":[91],"supervised":[92],"Imitation":[93],"as":[95],"an":[96],"initial":[97],"phase,":[98],"semi-realistic":[100],"model":[102],"13":[104],"screws":[106],"is":[107],"tuned,":[108],"fulfilling":[109],"both":[110],"insertion":[111],"loss":[112,115],"return":[114],"requirements.":[116],"On":[117],"problem,":[119],"algorithm":[121],"greater":[124],"efficiency":[125],"than":[126],"any":[127],"previously":[128],"published":[129],"for":[134],"tuning.":[137]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}