{"id":"https://openalex.org/W3194723232","doi":"https://doi.org/10.1109/icdl49984.2021.9515618","title":"Goal-Directed Planning by Predictive-Coding based Variational Recurrent Neural Network from Small Training Samples","display_name":"Goal-Directed Planning by Predictive-Coding based Variational Recurrent Neural Network from Small Training Samples","publication_year":2021,"publication_date":"2021-08-20","ids":{"openalex":"https://openalex.org/W3194723232","doi":"https://doi.org/10.1109/icdl49984.2021.9515618","mag":"3194723232"},"language":"en","primary_location":{"id":"doi:10.1109/icdl49984.2021.9515618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdl49984.2021.9515618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Development and Learning (ICDL)","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/A5013134800","display_name":"Keita Matsumoto","orcid":"https://orcid.org/0000-0002-0527-7418"},"institutions":[{"id":"https://openalex.org/I68926175","display_name":"Hoya (Japan)","ror":"https://ror.org/049vpfq31","country_code":"JP","type":"company","lineage":["https://openalex.org/I68926175"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Keita Matsumoto","raw_affiliation_strings":["Araya Inc., Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Araya Inc., Tokyo, Japan","institution_ids":["https://openalex.org/I68926175"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081769954","display_name":"Shinya Tamai","orcid":null},"institutions":[{"id":"https://openalex.org/I68926175","display_name":"Hoya (Japan)","ror":"https://ror.org/049vpfq31","country_code":"JP","type":"company","lineage":["https://openalex.org/I68926175"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shinya Tamai","raw_affiliation_strings":["Araya Inc., Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Araya Inc., Tokyo, Japan","institution_ids":["https://openalex.org/I68926175"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049957600","display_name":"Ryota Kanai","orcid":"https://orcid.org/0000-0002-0186-2687"},"institutions":[{"id":"https://openalex.org/I68926175","display_name":"Hoya (Japan)","ror":"https://ror.org/049vpfq31","country_code":"JP","type":"company","lineage":["https://openalex.org/I68926175"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryota Kanai","raw_affiliation_strings":["President and Representative Director, Araya Inc, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"President and Representative Director, Araya Inc, Tokyo, Japan","institution_ids":["https://openalex.org/I68926175"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5013134800"],"corresponding_institution_ids":["https://openalex.org/I68926175"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10810811,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9980999827384949,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9980999827384949,"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":0.9929999709129333,"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/T11431","display_name":"Action Observation and Synchronization","score":0.972100019454956,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.8525277972221375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7173033952713013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6095876693725586},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5702439546585083},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5268272757530212},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4523322582244873},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4509798586368561},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.44640398025512695},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4434196650981903},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.44017571210861206},{"id":"https://openalex.org/keywords/predictive-coding","display_name":"Predictive coding","score":0.418375700712204},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14569330215454102},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10635682940483093}],"concepts":[{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.8525277972221375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7173033952713013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6095876693725586},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5702439546585083},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5268272757530212},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4523322582244873},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4509798586368561},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.44640398025512695},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4434196650981903},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.44017571210861206},{"id":"https://openalex.org/C2778061373","wikidata":"https://www.wikidata.org/wiki/Q1315146","display_name":"Predictive coding","level":3,"score":0.418375700712204},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14569330215454102},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10635682940483093},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdl49984.2021.9515618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdl49984.2021.9515618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Development and Learning (ICDL)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320337495","display_name":"Technology Development","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1522301498","https://openalex.org/W1665214252","https://openalex.org/W1815076433","https://openalex.org/W1959608418","https://openalex.org/W2028418738","https://openalex.org/W2051228319","https://openalex.org/W2064675550","https://openalex.org/W2093072166","https://openalex.org/W2103617625","https://openalex.org/W2111947800","https://openalex.org/W2113266872","https://openalex.org/W2114414717","https://openalex.org/W2119885245","https://openalex.org/W2132960888","https://openalex.org/W2148764920","https://openalex.org/W2586360597","https://openalex.org/W2781726626","https://openalex.org/W2793412206","https://openalex.org/W2795910581","https://openalex.org/W2811120218","https://openalex.org/W2963277051","https://openalex.org/W2964257237","https://openalex.org/W2974745023","https://openalex.org/W2981344907","https://openalex.org/W3004214476","https://openalex.org/W3025794913","https://openalex.org/W3032377877","https://openalex.org/W3103942687","https://openalex.org/W4253020087","https://openalex.org/W6628877408","https://openalex.org/W6631190155","https://openalex.org/W6637242042","https://openalex.org/W6638545294","https://openalex.org/W6640963894","https://openalex.org/W6718092244","https://openalex.org/W6747473740","https://openalex.org/W6749450216","https://openalex.org/W6749629258","https://openalex.org/W6769596995","https://openalex.org/W6780226713"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W2086519370","https://openalex.org/W2028665553","https://openalex.org/W4225394202","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W2087343574"],"abstract_inverted_index":{"The":[0],"existing":[1],"goal-directed":[2,22,77],"planning":[3,23],"methods":[4],"using":[5,83,111],"predictive-coding-based":[6],"variational":[7],"recurrent":[8],"neural":[9],"network":[10],"(PV-RNN)":[11],"need":[12],"many":[13],"training":[14,29,36,62,81],"samples.":[15,30,63],"In":[16],"this":[17],"study,":[18],"we":[19,93],"propose":[20],"a":[21,89,112,116],"method":[24],"by":[25],"PV-RNN":[26,40,68,102],"from":[27,34,79],"small":[28,35,61,80],"To":[31,47,57],"achieve":[32],"generalization":[33],"samples,":[37],"the":[38,42,95,100],"proposed":[39,67,101],"integrates":[41],"following":[43],"two":[44],"ideas:":[45],"(1)":[46],"have":[48,58],"internal":[49],"models":[50],"based":[51],"on":[52],"kinematics":[53],"or":[54],"dynamics":[55],"(2)":[56],"diversity":[59],"in":[60,88],"We":[64],"evaluated":[65,94],"our":[66],"model":[69],"for":[70,115],"its":[71],"ability":[72],"to":[73,104],"generate":[74],"sufficiently":[75],"generalized":[76],"plans":[78],"samples":[82],"an":[84],"8-DOF":[85],"robot":[86,117],"arm":[87,118],"simulator":[90],"environment.":[91],"Furthermore,":[92],"advantages":[96],"and":[97,108],"disadvantages":[98],"of":[99],"compared":[103],"general":[105],"reinforcement":[106],"learning":[107,110],"imitation":[109],"benchmark":[113],"environment":[114],"task.":[119]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}