{"id":"https://openalex.org/W7128476674","doi":"https://doi.org/10.48550/arxiv.2602.07659","title":"Continuous Program Search","display_name":"Continuous Program Search","publication_year":2026,"publication_date":"2026-02-07","ids":{"openalex":"https://openalex.org/W7128476674","doi":"https://doi.org/10.48550/arxiv.2602.07659"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.07659","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.07659","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2602.07659","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124835722","display_name":"Matthew Siper","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siper, Matthew","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027180951","display_name":"Muhammad Umair Nasir","orcid":"https://orcid.org/0000-0002-2458-9599"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nasir, Muhammad Umair","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125487185","display_name":"Ahmed Khalifa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khalifa, Ahmed","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039317103","display_name":"L. B. Soros","orcid":"https://orcid.org/0000-0002-3259-3205"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Soros, Lisa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124835625","display_name":"Jay Azhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Azhang, Jay","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5098821073","display_name":"Julian Togelius","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Togelius, Julian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9599999785423279,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9599999785423279,"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":0.01119999960064888,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.0031999999191612005,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mutation","display_name":"Mutation","score":0.6686000227928162},{"id":"https://openalex.org/keywords/genetic-programming","display_name":"Genetic programming","score":0.5120000243186951},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4528999924659729},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.4392000138759613},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.43479999899864197},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.4343999922275543},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4205000102519989},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.39980000257492065},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.397599995136261}],"concepts":[{"id":"https://openalex.org/C501734568","wikidata":"https://www.wikidata.org/wiki/Q42918","display_name":"Mutation","level":3,"score":0.6686000227928162},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6047000288963318},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.5120000243186951},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48910000920295715},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4528999924659729},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.4392000138759613},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.43479999899864197},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.4343999922275543},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.39980000257492065},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.397599995136261},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.3828999996185303},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3756999969482422},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.367000013589859},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.34950000047683716},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3248000144958496},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.3224000036716461},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.3215000033378601},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.29109999537467957},{"id":"https://openalex.org/C163565370","wikidata":"https://www.wikidata.org/wiki/Q4308623","display_name":"Mutation testing","level":4,"score":0.29019999504089355},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2777000069618225},{"id":"https://openalex.org/C121835503","wikidata":"https://www.wikidata.org/wiki/Q2596288","display_name":"Evolutionary programming","level":3,"score":0.27649998664855957},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26600000262260437},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2615000009536743},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.25429999828338623},{"id":"https://openalex.org/C98638677","wikidata":"https://www.wikidata.org/wiki/Q2067051","display_name":"Mutation rate","level":3,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.07659","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.07659","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.07659","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.07659","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Genetic":[0],"Programming":[1],"yields":[2,169],"interpretable":[3],"programs,":[4],"but":[5],"small":[6],"syntactic":[7],"mutations":[8],"can":[9,179],"induce":[10],"large,":[11],"unpredictable":[12],"behavioral":[13,36],"shifts,":[14],"degrading":[15],"locality":[16,53],"and":[17,83,91,112,130,151],"sample":[18],"efficiency.":[19],"We":[20,51],"frame":[21],"this":[22,44],"as":[23],"an":[24,64,145],"operator-design":[25],"problem:":[26],"learn":[27,86],"a":[28,73,87,116],"continuous":[29,70],"program":[30],"space":[31,100],"where":[32],"latent":[33,61,99],"distance":[34],"has":[35],"meaning,":[37],"then":[38],"design":[39],"mutation":[40,95,103,123,139,161,168,178],"operators":[41],"that":[42,104,175],"exploit":[43],"structure":[45],"without":[46,184],"changing":[47],"the":[48,97,137,153,186],"evolutionary":[49,188],"optimizer.":[50],"make":[52],"measurable":[54],"by":[55],"tracking":[56],"action-level":[57],"divergence":[58],"under":[59],"controlled":[60],"perturbations,":[62],"identifying":[63],"empirical":[65],"trust":[66],"region":[67],"for":[68],"behavior-local":[69],"variation.":[71],"Using":[72],"compact":[74],"trading-strategy":[75],"DSL":[76],"with":[77],"four":[78],"semantic":[79],"components":[80],"(long/short":[81],"entry":[82],"exit),":[84],"we":[85],"matching":[88],"block-factorized":[89],"embedding":[90],"compare":[92],"isotropic":[93,160],"Gaussian":[94],"over":[96],"full":[98],"to":[101,107],"geometry-compiled":[102,167],"restricts":[105],"updates":[106],"semantically":[108,176],"paired":[109],"entry--exit":[110],"subspaces":[111],"proposes":[113],"directions":[114],"using":[115,144],"learned":[117,138],"flow-based":[118],"model":[119],"trained":[120],"on":[121],"logged":[122],"outcomes.":[124],"Under":[125],"identical":[126],"$(\u03bc+\u03bb)$":[127],"evolution":[128],"strategies":[129,143],"fixed":[131],"evaluation":[132],"budgets":[133],"across":[134],"five":[135],"assets,":[136],"operator":[140],"discovers":[141],"strong":[142],"order":[146],"of":[147],"magnitude":[148],"fewer":[149],"evaluations":[150],"achieves":[152],"highest":[154],"median":[155],"out-of-sample":[156],"Sharpe":[157],"ratio.":[158],"Although":[159],"occasionally":[162],"attains":[163],"higher":[164],"peak":[165],"performance,":[166],"faster,":[170],"more":[171],"reliable":[172],"progress,":[173],"demonstrating":[174],"aligned":[177],"substantially":[180],"improve":[181],"search":[182],"efficiency":[183],"modifying":[185],"underlying":[187],"algorithm.":[189]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-02-11T00:00:00"}