{"id":"https://openalex.org/W4410152222","doi":"https://doi.org/10.1145/3716550.3722012","title":"Accelerating Neural Policy Repair with Preservation via Stability-Plasticity Interpolation","display_name":"Accelerating Neural Policy Repair with Preservation via Stability-Plasticity Interpolation","publication_year":2025,"publication_date":"2025-05-06","ids":{"openalex":"https://openalex.org/W4410152222","doi":"https://doi.org/10.1145/3716550.3722012"},"language":"en","primary_location":{"id":"doi:10.1145/3716550.3722012","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3716550.3722012","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3716550.3722012","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM/IEEE 16th International Conference on Cyber-Physical Systems (with CPS-IoT Week 2025)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3716550.3722012","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081521997","display_name":"Pengyuan Lu","orcid":"https://orcid.org/0000-0003-2795-6339"},"institutions":[{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pengyuan Lu","raw_affiliation_strings":["University of Pennsylvania"],"raw_orcid":"https://orcid.org/0000-0003-2795-6339","affiliations":[{"raw_affiliation_string":"University of Pennsylvania","institution_ids":["https://openalex.org/I36788626"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082105260","display_name":"Oleg Sokolsky","orcid":"https://orcid.org/0000-0001-5282-0658"},"institutions":[{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Oleg Sokolsky","raw_affiliation_strings":["University of Pennsylvania"],"raw_orcid":"https://orcid.org/0000-0001-5282-0658","affiliations":[{"raw_affiliation_string":"University of Pennsylvania","institution_ids":["https://openalex.org/I36788626"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030456600","display_name":"Insup Lee","orcid":"https://orcid.org/0000-0003-2672-1132"},"institutions":[{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Insup Lee","raw_affiliation_strings":["University of Pennsylvania"],"raw_orcid":"https://orcid.org/0000-0003-2672-1132","affiliations":[{"raw_affiliation_string":"University of Pennsylvania","institution_ids":["https://openalex.org/I36788626"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021509994","display_name":"Ivan Ruchkin","orcid":"https://orcid.org/0000-0003-3546-414X"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ivan Ruchkin","raw_affiliation_strings":["University of Florida"],"raw_orcid":"https://orcid.org/0000-0003-3546-414X","affiliations":[{"raw_affiliation_string":"University of Florida","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9980000257492065,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9980000257492065,"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"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9980000257492065,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9962000250816345,"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/stability","display_name":"Stability (learning theory)","score":0.621308445930481},{"id":"https://openalex.org/keywords/plasticity","display_name":"Plasticity","score":0.6125222444534302},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.564856231212616},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.499345064163208},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2252516746520996},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.18888789415359497},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.09510597586631775}],"concepts":[{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.621308445930481},{"id":"https://openalex.org/C79186407","wikidata":"https://www.wikidata.org/wiki/Q472074","display_name":"Plasticity","level":2,"score":0.6125222444534302},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.564856231212616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.499345064163208},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2252516746520996},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.18888789415359497},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.09510597586631775},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3716550.3722012","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3716550.3722012","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3716550.3722012","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM/IEEE 16th International Conference on Cyber-Physical Systems (with CPS-IoT Week 2025)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3716550.3722012","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3716550.3722012","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3716550.3722012","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM/IEEE 16th International Conference on Cyber-Physical Systems (with CPS-IoT Week 2025)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.49000000953674316,"display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G172421478","display_name":"Collaborative Research: CPS: Small: Neuro-Symbolic Bridge: From Perception to Estimation & Control","funder_award_id":"2403616","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G294481052","display_name":"Collaborative Research: CPS: Medium: Sensor Attack Detection and Recovery in Cyber-Physical Systems","funder_award_id":"2143274","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4941497083","display_name":null,"funder_award_id":"CCF-2403616","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6074853558","display_name":null,"funder_award_id":"W911NF-20-1-0080","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G7452299184","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G8557483749","display_name":null,"funder_award_id":"CNS-2143274,CCF-2403616","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G960819809","display_name":null,"funder_award_id":"ARO W911NF-20-1-0080","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410152222.pdf","grobid_xml":"https://content.openalex.org/works/W4410152222.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1511887321","https://openalex.org/W1528053940","https://openalex.org/W1547304883","https://openalex.org/W2049399166","https://openalex.org/W2524910163","https://openalex.org/W2560647685","https://openalex.org/W2604382266","https://openalex.org/W2842089854","https://openalex.org/W2962775887","https://openalex.org/W2963186766","https://openalex.org/W3030364939","https://openalex.org/W3100789280","https://openalex.org/W3184441520","https://openalex.org/W3211766227","https://openalex.org/W4236965008","https://openalex.org/W4296963693","https://openalex.org/W4400189298"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2016937053","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W2372312044","https://openalex.org/W2098828199","https://openalex.org/W4396701345"],"abstract_inverted_index":{"Neural":[0],"network":[1],"(NN)":[2],"control":[3],"has":[4,106],"been":[5,107],"adopted":[6],"widely":[7],"in":[8,109,163,179],"cyberphysical":[9],"systems":[10],"(CPS).":[11],"When":[12],"an":[13,146,185],"NN-based":[14],"policy":[15],"fails":[16],"a":[17,48,84,99,169],"formally":[18],"specified":[19],"task,":[20],"NN":[21,86,155,159,171],"repair":[22],"algorithms":[23],"can":[24],"fix":[25],"it.":[26],"Recent":[27],"literature":[28],"raises":[29],"the":[30,45,65,95,128,149,153,157,164,205,210],"problem":[31,97],"of":[32,69,148,204,218],"Repair":[33,58],"with":[34,119,215],"Preservation":[35],"(RwP),":[36],"which":[37,71,105,122],"requires":[38],"preserving":[39],"existing":[40],"correct":[41,88,141],"behaviors":[42,142],"while":[43,199],"repairing":[44,200],"incorrect":[46],"ones;":[47],"corresponding":[49],"solution":[50],"is":[51,160,192],"given,":[52],"known":[53],"as":[54,213],"Incremental":[55],"Simulated":[56],"Annealing":[57],"(ISAR).":[59],"In":[60],"this":[61],"paper,":[62],"we":[63,93,114],"tackle":[64],"computational":[66,79],"efficiency":[67],"issue":[68],"ISAR,":[70,214],"involves":[72],"expensive":[73,129],"log-barriered":[74],"objective":[75],"functions":[76],"and":[77,132,156,175,184,202,221],"wastes":[78],"efforts":[80],"rolling":[81],"back":[82,134],"when":[83],"repaired":[85],"breaks":[87],"behaviors.":[89],"With":[90],"our":[91,116],"analysis,":[92],"reduce":[94],"RwP":[96],"to":[98,135,139,194],"stability-plasticity":[100],"(S-P)":[101],"trade-off":[102,151],"interpolation":[103,147],"problem,":[104],"studied":[108],"continual":[110],"learning":[111],"(CL).":[112],"Then,":[113,145],"propose":[115],"method,":[117],"ISAR":[118],"Interpolation":[120],"(ISAR-I),":[121],"majorly":[123],"improves":[124],"ISAR.":[125],"ISAR-I":[126,191],"abandons":[127],"log":[130],"barriers":[131],"rolls":[133],"allow":[136],"intermediate":[137,158],"policies":[138],"compromise":[140],"for":[143,168],"repair.":[144],"S-P":[150],"between":[152],"original":[154],"kicked":[161],"off":[162],"Bayesian":[165],"space,":[166],"searching":[167],"final":[170],"that":[172,190],"both":[173],"repairs":[174],"preserves.":[176],"Case":[177],"studies":[178],"OpenAI":[180],"Gym":[181],"mountain":[182],"car":[183],"unmanned":[186],"underwater":[187],"vehicle":[188],"show":[189],"able":[193],"preserve":[195],"all":[196],"verified":[197],"trajectories":[198],"81.7%":[201],"21.3%":[203],"broken":[206],"ones,":[207],"respectively,":[208],"achieving":[209],"same":[211],"performance":[212],"runtime":[216],"cost":[217],"only":[219],"6.5%":[220],"19.6%,":[222],"on":[223],"average.":[224],"Source":[225],"code:":[226],"https://github.com/ericlupy/isar_interpolation":[227]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}