{"id":"https://openalex.org/W2978020414","doi":"https://doi.org/10.1109/devlrn.2019.8850676","title":"Action Selection Based on Prediction for Robot Planning","display_name":"Action Selection Based on Prediction for Robot Planning","publication_year":2019,"publication_date":"2019-08-01","ids":{"openalex":"https://openalex.org/W2978020414","doi":"https://doi.org/10.1109/devlrn.2019.8850676","mag":"2978020414"},"language":"en","primary_location":{"id":"doi:10.1109/devlrn.2019.8850676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/devlrn.2019.8850676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)","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/A5075117112","display_name":"Mengxi Nie","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mengxi Nie","raw_affiliation_strings":["Department of Machine Intelligence, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Machine Intelligence, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004014436","display_name":"Dingsheng Luo","orcid":"https://orcid.org/0000-0001-6997-3984"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dingsheng Luo","raw_affiliation_strings":["Department of Machine Intelligence, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Machine Intelligence, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101848357","display_name":"Tianlin Liu","orcid":"https://orcid.org/0000-0001-8231-7594"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianlin Liu","raw_affiliation_strings":["Department of Machine Intelligence, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Machine Intelligence, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084685506","display_name":"Xihong Wu","orcid":"https://orcid.org/0009-0004-5236-7469"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xihong Wu","raw_affiliation_strings":["Department of Machine Intelligence, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Machine Intelligence, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5075117112"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.1663,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.4884465,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"23","issue":null,"first_page":"201","last_page":"206"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9998999834060669,"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":0.9998999834060669,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9966999888420105,"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/computer-science","display_name":"Computer science","score":0.7240133881568909},{"id":"https://openalex.org/keywords/action-selection","display_name":"Action selection","score":0.711584746837616},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.710019588470459},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.6941552758216858},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6874343156814575},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5574893951416016},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4911513030529022},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46574389934539795},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4651162922382355},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44670212268829346}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7240133881568909},{"id":"https://openalex.org/C166109690","wikidata":"https://www.wikidata.org/wiki/Q4677422","display_name":"Action selection","level":3,"score":0.711584746837616},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.710019588470459},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.6941552758216858},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6874343156814575},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5574893951416016},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4911513030529022},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46574389934539795},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4651162922382355},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44670212268829346},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","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},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/devlrn.2019.8850676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/devlrn.2019.8850676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)","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":26,"referenced_works":["https://openalex.org/W69711126","https://openalex.org/W1499079881","https://openalex.org/W1558620469","https://openalex.org/W1638373997","https://openalex.org/W1979592787","https://openalex.org/W2011804970","https://openalex.org/W2021949268","https://openalex.org/W2064675550","https://openalex.org/W2065804258","https://openalex.org/W2081817157","https://openalex.org/W2093794457","https://openalex.org/W2103185595","https://openalex.org/W2109087172","https://openalex.org/W2153340051","https://openalex.org/W2470271743","https://openalex.org/W2505308623","https://openalex.org/W2741471233","https://openalex.org/W2781682462","https://openalex.org/W2809232767","https://openalex.org/W2959133662","https://openalex.org/W3132347552","https://openalex.org/W4233172861","https://openalex.org/W6633428597","https://openalex.org/W6636948731","https://openalex.org/W6655983294","https://openalex.org/W6675890081"],"related_works":["https://openalex.org/W2235786","https://openalex.org/W9321062","https://openalex.org/W6296663","https://openalex.org/W8821115","https://openalex.org/W2623355","https://openalex.org/W10379689","https://openalex.org/W102453","https://openalex.org/W12522828","https://openalex.org/W13478224","https://openalex.org/W2084237"],"abstract_inverted_index":{"In":[0,66],"this":[1,91],"work":[2],"we":[3],"focus":[4],"on":[5,54,106,126],"the":[6,15,18,39,46,55,80,94,100,107,112,130,139],"action":[7,42,52],"selection":[8,43],"process":[9],"of":[10,20,41,82,90,96,115,132,143],"a":[11,68],"robot":[12,16,47,85,101,144],"by":[13],"equipping":[14],"with":[17,26],"ability":[19],"internal":[21,27,120],"prediction.":[22,56],"A":[23,87],"novel":[24],"approach":[25],"simulation":[28],"is":[29,75,93],"proposed,":[30],"in":[31,119],"which":[32],"Conditional":[33],"Generative":[34],"Adversarial":[35],"Nets":[36],"(CGANs)":[37],"provides":[38],"possibility":[40],"and":[44,110,141],"allows":[45],"to":[48,59,77,128],"choose":[49],"an":[50],"optimal":[51],"based":[53,105],"This":[57],"leads":[58],"robots":[60],"that":[61,136],"can":[62],"perform":[63],"tasks":[64],"better.":[65],"addition,":[67],"structure":[69],"containing":[70],"recurrent":[71],"neural":[72],"network":[73],"(RNN)":[74],"used":[76],"further":[78],"predict":[79],"sequence":[81],"actions":[83,104,118],"for":[84],"planning.":[86],"key":[88],"feature":[89],"model":[92],"incorporation":[95],"sensorimotor":[97],"prediction,":[98],"where":[99],"generates":[102],"corresponding":[103],"current":[108],"context":[109],"anticipates":[111],"sensory":[113],"consequences":[114],"currently":[116],"executable":[117],"simulation.":[121],"Experiments":[122],"have":[123],"been":[124],"conducted":[125],"PKU-HR6.0":[127],"verify":[129],"effectiveness":[131],"our":[133],"approach,":[134],"showing":[135],"it":[137],"improves":[138],"accuracy":[140],"speed":[142],"arm":[145],"reaching.":[146]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}