{"id":"https://openalex.org/W2806252546","doi":"https://doi.org/10.1109/amc.2019.8371085","title":"Optimal routing control of a construction machine by deep reinforcement learning","display_name":"Optimal routing control of a construction machine by deep reinforcement learning","publication_year":2018,"publication_date":"2018-03-01","ids":{"openalex":"https://openalex.org/W2806252546","doi":"https://doi.org/10.1109/amc.2019.8371085","mag":"2806252546"},"language":"en","primary_location":{"id":"doi:10.1109/amc.2019.8371085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/amc.2019.8371085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Workshop on Advanced Motion Control (AMC)","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/A5014984172","display_name":"Zeyuan Sun","orcid":"https://orcid.org/0000-0003-4938-153X"},"institutions":[{"id":"https://openalex.org/I171481255","display_name":"Shibaura Institute of Technology","ror":"https://ror.org/020wjcq07","country_code":"JP","type":"education","lineage":["https://openalex.org/I171481255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zeyuan Sun","raw_affiliation_strings":["Shibaura Institute of Technology, Koto-ku, Tokyo, JAPAN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shibaura Institute of Technology, Koto-ku, Tokyo, JAPAN","institution_ids":["https://openalex.org/I171481255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005878573","display_name":"Masayuki Nakatani","orcid":null},"institutions":[{"id":"https://openalex.org/I171481255","display_name":"Shibaura Institute of Technology","ror":"https://ror.org/020wjcq07","country_code":"JP","type":"education","lineage":["https://openalex.org/I171481255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masayuki Nakatani","raw_affiliation_strings":["Shibaura Institute of Technology, Koto-ku, Tokyo, JAPAN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shibaura Institute of Technology, Koto-ku, Tokyo, JAPAN","institution_ids":["https://openalex.org/I171481255"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110775550","display_name":"Yutaka Uchimura","orcid":null},"institutions":[{"id":"https://openalex.org/I171481255","display_name":"Shibaura Institute of Technology","ror":"https://ror.org/020wjcq07","country_code":"JP","type":"education","lineage":["https://openalex.org/I171481255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yutaka Uchimura","raw_affiliation_strings":["Shibaura Institute of Technology, Koto-ku, Tokyo, JAPAN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shibaura Institute of Technology, Koto-ku, Tokyo, JAPAN","institution_ids":["https://openalex.org/I171481255"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I171481255"],"apc_list":null,"apc_paid":null,"fwci":0.3747,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59638434,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":95},"biblio":{"volume":"37","issue":null,"first_page":"187","last_page":"192"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11749","display_name":"Iterative Learning Control Systems","score":0.9668999910354614,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11749","display_name":"Iterative Learning Control Systems","score":0.9668999910354614,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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":0.9621000289916992,"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/T10409","display_name":"Fuel Cells and Related Materials","score":0.9502000212669373,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/grading","display_name":"Grading (engineering)","score":0.8376624584197998},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8146238327026367},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7606468200683594},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.6049293875694275},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5524889826774597},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4675041139125824},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16247069835662842}],"concepts":[{"id":"https://openalex.org/C2777286243","wikidata":"https://www.wikidata.org/wiki/Q5591926","display_name":"Grading (engineering)","level":2,"score":0.8376624584197998},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8146238327026367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7606468200683594},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6049293875694275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5524889826774597},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4675041139125824},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16247069835662842},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/amc.2019.8371085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/amc.2019.8371085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Workshop on Advanced Motion Control (AMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5899999737739563,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334900","display_name":"Japan Aerospace Exploration Agency","ror":"https://ror.org/059yhyy33"},{"id":"https://openalex.org/F4320338245","display_name":"Support Program for Starting up Innovation Hub","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W1605318140","https://openalex.org/W1836465849","https://openalex.org/W2041387425","https://openalex.org/W2047983719","https://openalex.org/W2127412976","https://openalex.org/W2145339207","https://openalex.org/W2155968351","https://openalex.org/W2163605009","https://openalex.org/W2173248099","https://openalex.org/W2173564293","https://openalex.org/W2257979135","https://openalex.org/W2260756217","https://openalex.org/W2284050935","https://openalex.org/W2746553466","https://openalex.org/W2761873684","https://openalex.org/W2766447205","https://openalex.org/W2951799221","https://openalex.org/W2963864421","https://openalex.org/W2964043796","https://openalex.org/W3009585715","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Deep":[0],"reinforcement":[1],"learning":[2,53],"algorithms":[3],"are":[4],"rapidly":[5],"growing,":[6],"and":[7,74],"expected":[8],"to":[9,12,31,43,60],"be":[10],"applied":[11],"many":[13],"industrial":[14],"fields.":[15],"In":[16],"this":[17],"paper,":[18],"we":[19],"proposed":[20,66],"a":[21,25,37,55],"method":[22,67],"that":[23],"combines":[24],"deep":[26],"Q-network":[27],"with":[28,70],"batch":[29],"normalization":[30],"generate":[32],"an":[33],"optimal":[34],"route":[35,77],"for":[36],"grading":[38,49,56,63,72],"machine.":[39,50],"The":[40,65],"goal":[41],"is":[42],"achieve":[44],"autonomous":[45],"operation":[46],"of":[47],"the":[48,52,62,71,82],"For":[51],"platform,":[54],"simulator":[57],"was":[58,68],"developed":[59],"emulate":[61],"work.":[64],"evaluated":[69],"simulator,":[73],"showed":[75],"better":[76],"searching":[78],"performance":[79],"results":[80],"than":[81],"conventional":[83],"method.":[84]},"counts_by_year":[{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
