{"id":"https://openalex.org/W4413321408","doi":"https://doi.org/10.1109/cog64752.2025.11114167","title":"A Continual Offline Reinforcement Learning Benchmark for Navigation Tasks","display_name":"A Continual Offline Reinforcement Learning Benchmark for Navigation Tasks","publication_year":2025,"publication_date":"2025-08-19","ids":{"openalex":"https://openalex.org/W4413321408","doi":"https://doi.org/10.1109/cog64752.2025.11114167"},"language":"en","primary_location":{"id":"doi:10.1109/cog64752.2025.11114167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cog64752.2025.11114167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Conference on Games (CoG)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-05126447/document","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070675436","display_name":"Anthony Kobanda","orcid":"https://orcid.org/0000-0001-5899-160X"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I2279609970","display_name":"Universit\u00e9 de Lille","ror":"https://ror.org/02kzqn938","country_code":"FR","type":"education","lineage":["https://openalex.org/I2279609970"]},{"id":"https://openalex.org/I7454413","display_name":"\u00c9cole Centrale de Lille","ror":"https://ror.org/01x441g73","country_code":"FR","type":"education","lineage":["https://openalex.org/I7454413"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Anthony Kobanda","raw_affiliation_strings":["Inria, Univ. Lille, CNRS, UMR 9198-CRIStAL,Centrale Lille,Lille,France,F-59000"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inria, Univ. Lille, CNRS, UMR 9198-CRIStAL,Centrale Lille,Lille,France,F-59000","institution_ids":["https://openalex.org/I2279609970","https://openalex.org/I7454413","https://openalex.org/I1294671590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055126334","display_name":"Odalric-Ambrym Maillard","orcid":null},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I2279609970","display_name":"Universit\u00e9 de Lille","ror":"https://ror.org/02kzqn938","country_code":"FR","type":"education","lineage":["https://openalex.org/I2279609970"]},{"id":"https://openalex.org/I7454413","display_name":"\u00c9cole Centrale de Lille","ror":"https://ror.org/01x441g73","country_code":"FR","type":"education","lineage":["https://openalex.org/I7454413"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Odalric-Ambrym Maillard","raw_affiliation_strings":["Inria, Univ. Lille, CNRS, UMR 9198-CRIStAL,Centrale Lille,Lille,France,F-59000"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inria, Univ. Lille, CNRS, UMR 9198-CRIStAL,Centrale Lille,Lille,France,F-59000","institution_ids":["https://openalex.org/I2279609970","https://openalex.org/I7454413","https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006159402","display_name":"R\u00e9my Portelas","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104997","display_name":"Ubisoft (France)","ror":"https://ror.org/01s40r185","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210104997"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"R\u00e9my Portelas","raw_affiliation_strings":["Ubisoft La Forge,Bordeaux,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ubisoft La Forge,Bordeaux,France","institution_ids":["https://openalex.org/I4210104997"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070675436"],"corresponding_institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I2279609970","https://openalex.org/I7454413"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18228825,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9587000012397766,"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"}},"topics":[{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9587000012397766,"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":0.9348000288009644,"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":0.8745553493499756},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7969195246696472},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.750401496887207},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5546735525131226},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5135319828987122}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8745553493499756},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7969195246696472},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.750401496887207},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5546735525131226},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5135319828987122},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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":3,"locations":[{"id":"doi:10.1109/cog64752.2025.11114167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cog64752.2025.11114167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Conference on Games (CoG)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-05126447v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05126447","pdf_url":"https://hal.science/hal-05126447/document","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Conference on Games, Aug 2025, Lisboa, Portugal","raw_type":"Conference papers"},{"id":"pmh:doi:10.48550/arxiv.2506.02883","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-05126447v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05126447","pdf_url":"https://hal.science/hal-05126447/document","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Conference on Games, Aug 2025, Lisboa, Portugal","raw_type":"Conference papers"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4413321408.pdf","grobid_xml":"https://content.openalex.org/works/W4413321408.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2560647685","https://openalex.org/W2743151379","https://openalex.org/W2963871073","https://openalex.org/W3094321564","https://openalex.org/W3100789280","https://openalex.org/W3117215073","https://openalex.org/W3173369353","https://openalex.org/W3205279237","https://openalex.org/W4285601030","https://openalex.org/W4389315227","https://openalex.org/W4392173735","https://openalex.org/W4401943470"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Autonomous":[0],"agents":[1],"operating":[2],"in":[3,63,113],"domains":[4],"such":[5],"as":[6],"robotics":[7],"or":[8],"video":[9],"game":[10],"simulations":[11],"must":[12],"adapt":[13],"to":[14,36,90,105,110,121,131,134],"changing":[15],"tasks":[16,83],"without":[17],"forgetting":[18,35],"about":[19],"the":[20,38,41,64,92],"previous":[21],"ones.":[22],"This":[23],"process":[24],"called":[25],"Continual":[26],"Reinforcement":[27],"Learning":[28],"poses":[29],"non-trivial":[30],"difficulties,":[31],"from":[32],"preventing":[33],"catastrophic":[34,70],"ensuring":[37],"scalability":[39],"of":[40,55,81,94],"approaches":[42],"considered.":[43],"Building":[44],"on":[45],"recent":[46],"advances,":[47],"we":[48],"introduce":[49],"a":[50,53,61,79,123],"benchmark":[51,100],"providing":[52],"suite":[54],"video-game":[56],"navigation":[57],"scenarios,":[58],"thus":[59],"filling":[60],"gap":[62],"literature":[65],"and":[66,74,84,88,109,133],"capturing":[67],"key":[68],"challenges:":[69],"forgetting,":[71],"task":[72],"adaptation,":[73],"memory":[75],"efficiency.":[76],"We":[77],"define":[78],"set":[80],"various":[82],"datasets,":[85],"evaluation":[86],"protocols,":[87],"metrics":[89],"assess":[91],"performance":[93],"algorithms,":[95],"including":[96],"state-of-the-art":[97],"baselines.":[98],"Our":[99],"is":[101],"designed":[102],"not":[103],"only":[104],"foster":[106],"reproducible":[107,124],"research":[108],"accelerate":[111],"progress":[112],"continual":[114],"reinforcement":[115],"learning":[116],"for":[117,126],"gaming,":[118],"but":[119],"also":[120],"provide":[122],"framework":[125],"production":[127],"pipelines":[128],"helping":[129],"practitioners":[130],"identify":[132],"apply":[135],"effective":[136],"approaches.":[137],"https://sites.google.com/view/continual-nav-bench":[138]},"counts_by_year":[],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2025-10-10T00:00:00"}