{"id":"https://openalex.org/W4408995462","doi":"https://doi.org/10.3390/e27040367","title":"From Task Distributions to Expected Paths Lengths Distributions: Value Function Initialization in Sparse Reward Environments for Lifelong Reinforcement Learning","display_name":"From Task Distributions to Expected Paths Lengths Distributions: Value Function Initialization in Sparse Reward Environments for Lifelong Reinforcement Learning","publication_year":2025,"publication_date":"2025-03-30","ids":{"openalex":"https://openalex.org/W4408995462","doi":"https://doi.org/10.3390/e27040367","pmid":"https://pubmed.ncbi.nlm.nih.gov/40282602"},"language":"en","primary_location":{"id":"doi:10.3390/e27040367","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e27040367","pdf_url":"https://www.mdpi.com/1099-4300/27/4/367/pdf?version=1743324862","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/27/4/367/pdf?version=1743324862","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075037239","display_name":"Soumia Mehimeh","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Soumia Mehimeh","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, 92 West Dazhi Street, Nangang District, Harbin 150001, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, 92 West Dazhi Street, Nangang District, Harbin 150001, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100873220","display_name":"Xianglong Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianglong Tang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, 92 West Dazhi Street, Nangang District, Harbin 150001, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, 92 West Dazhi Street, Nangang District, Harbin 150001, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075037239"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0274507,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":"4","first_page":"367","last_page":"367"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.8614000082015991,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.8614000082015991,"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/initialization","display_name":"Initialization","score":0.7559822797775269},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7030826210975647},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6749284267425537},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5663792490959167},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5275067090988159},{"id":"https://openalex.org/keywords/bellman-equation","display_name":"Bellman equation","score":0.5126923322677612},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4915538728237152},{"id":"https://openalex.org/keywords/expected-value","display_name":"Expected value","score":0.4528995752334595},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4484342932701111},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.4444800019264221},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4295109212398529},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33903390169143677},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26976442337036133},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16813182830810547}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7559822797775269},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7030826210975647},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6749284267425537},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5663792490959167},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5275067090988159},{"id":"https://openalex.org/C14646407","wikidata":"https://www.wikidata.org/wiki/Q1430750","display_name":"Bellman equation","level":2,"score":0.5126923322677612},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4915538728237152},{"id":"https://openalex.org/C141042865","wikidata":"https://www.wikidata.org/wiki/Q200125","display_name":"Expected value","level":2,"score":0.4528995752334595},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4484342932701111},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.4444800019264221},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4295109212398529},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33903390169143677},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26976442337036133},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16813182830810547},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/e27040367","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e27040367","pdf_url":"https://www.mdpi.com/1099-4300/27/4/367/pdf?version=1743324862","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:40282602","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40282602","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:857756d1024d432f85c93402387d4d17","is_oa":true,"landing_page_url":"https://doaj.org/article/857756d1024d432f85c93402387d4d17","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 27, Iss 4, p 367 (2025)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:12025380","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12025380","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e27040367","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e27040367","pdf_url":"https://www.mdpi.com/1099-4300/27/4/367/pdf?version=1743324862","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4408995462.pdf"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W2760355785","https://openalex.org/W2967727187","https://openalex.org/W3027406032","https://openalex.org/W3117215073","https://openalex.org/W3175458185","https://openalex.org/W3212580602","https://openalex.org/W4220923746","https://openalex.org/W4285601030","https://openalex.org/W4383112908","https://openalex.org/W4383535181","https://openalex.org/W4385768110","https://openalex.org/W4387213019","https://openalex.org/W6630103346","https://openalex.org/W6674600207","https://openalex.org/W6676875888","https://openalex.org/W6678481081","https://openalex.org/W6683300800","https://openalex.org/W6740801417","https://openalex.org/W6751617248","https://openalex.org/W6754287037","https://openalex.org/W6760698134","https://openalex.org/W6797437937","https://openalex.org/W6839812418","https://openalex.org/W6842837606","https://openalex.org/W6846493773","https://openalex.org/W6846881803","https://openalex.org/W6847296024","https://openalex.org/W6849493766","https://openalex.org/W6853121553","https://openalex.org/W6858183715"],"related_works":["https://openalex.org/W2386410636","https://openalex.org/W3038962357","https://openalex.org/W2025663273","https://openalex.org/W3099153698","https://openalex.org/W3121993784","https://openalex.org/W3125259243","https://openalex.org/W2783273658","https://openalex.org/W4297665515","https://openalex.org/W2243595037","https://openalex.org/W10913952"],"abstract_inverted_index":{"This":[0,114],"paper":[1],"studies":[2],"value":[3,47,131,146,188],"function":[4,48,132,147,189],"transfer":[5,148],"within":[6],"reinforcement":[7],"learning":[8],"frameworks,":[9],"focusing":[10],"on":[11,25,151,160],"tasks":[12],"continuously":[13],"assigned":[14],"to":[15,76,118],"an":[16,173],"agent":[17],"through":[18],"a":[19,32,134,144,161,174],"probabilistic":[20],"distribution.":[21],"Specifically,":[22],"we":[23,36,85,96,140,157],"focus":[24],"environments":[26],"characterized":[27],"by":[28,80,171],"sparse":[29],"rewards":[30],"with":[31],"terminal":[33],"goal.":[34],"Initially,":[35],"propose":[37,119],"and":[38,165,180,193],"theoretically":[39],"demonstrate":[40,181],"that":[41,98,120,182],"the":[42,45,56,59,69,72,77,87,99,102,109,122,127,130,152,178],"distribution":[43,70,100,111,123,128],"of":[44,71,74,101,129,154,163,177,187],"computed":[46],"from":[49,108],"such":[50],"environments,":[51],"whether":[52],"in":[53],"cases":[54],"where":[55],"goals":[57,164],"or":[58],"dynamics":[60,166],"are":[61],"changing":[62],"across":[63],"tasks,":[64],"can":[65],"be":[66],"reformulated":[67],"as":[68,143],"number":[73],"steps":[75],"goal":[78],"generated":[79],"their":[81],"optimal":[82,89,104],"policies,":[83],"which":[84],"name":[86],"<i>expected":[88],"path":[90,105],"length</i>.":[91],"To":[92],"test":[93],"our":[94,169],"propositions,":[95],"hypothesize":[97],"expected":[103],"lengths":[106],"resulting":[107],"task":[110],"is":[112,124],"normal.":[113],"claim":[115],"leads":[116],"us":[117],"if":[121],"normal,":[125],"then":[126],"follows":[133],"log-normal":[135],"pattern.":[136],"Leveraging":[137],"this":[138],"insight,":[139],"introduce":[141],"\"LogQInit\"":[142],"novel":[145],"method,":[149],"based":[150],"properties":[153],"log-normality.":[155],"Finally,":[156],"run":[158],"experiments":[159],"scenario":[162],"distributions,":[167],"validate":[168],"proposition":[170],"providing":[172],"dequate":[175],"analysis":[176],"results,":[179],"LogQInit":[183],"outperforms":[184],"existing":[185],"methods":[186],"initialization,":[190],"policy":[191],"transfer,":[192],"reward":[194],"shaping.":[195]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}