{"id":"https://openalex.org/W7162766506","doi":"https://doi.org/10.48550/arxiv.2605.29268","title":"Compute Allocation in Evolutionary Search: From Depth-Breadth to Multi-Armed Bandits","display_name":"Compute Allocation in Evolutionary Search: From Depth-Breadth to Multi-Armed Bandits","publication_year":2026,"publication_date":"2026-05-28","ids":{"openalex":"https://openalex.org/W7162766506","doi":"https://doi.org/10.48550/arxiv.2605.29268"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.29268","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29268","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2605.29268","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137364700","display_name":"Sixue Xing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xing, Sixue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137383695","display_name":"Haoyu He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Haoyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137363215","display_name":"Kerui Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Kerui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137348100","display_name":"Zhuo Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Zhuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137318586","display_name":"Haozheng Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Haozheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137365523","display_name":"Tianfan Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Tianfan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5068520773","display_name":"Aarthy Nagarajan","orcid":"https://orcid.org/0000-0003-4649-060X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nagarajan, Aarthy","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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.27309998869895935,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.27309998869895935,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.20180000364780426,"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"}},{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.12150000035762787,"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/base","display_name":"Base (topology)","score":0.5379999876022339},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5049999952316284},{"id":"https://openalex.org/keywords/ask-price","display_name":"Ask price","score":0.5013999938964844},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5011000037193298},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.4489000141620636},{"id":"https://openalex.org/keywords/envelope","display_name":"Envelope (radar)","score":0.4375},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.4318000078201294},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.3813000023365021}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5665000081062317},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.5379999876022339},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5049999952316284},{"id":"https://openalex.org/C90329073","wikidata":"https://www.wikidata.org/wiki/Q914232","display_name":"Ask price","level":2,"score":0.5013999938964844},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5011000037193298},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.46140000224113464},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.4489000141620636},{"id":"https://openalex.org/C65155139","wikidata":"https://www.wikidata.org/wiki/Q5380912","display_name":"Envelope (radar)","level":3,"score":0.4375},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4318000078201294},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3813000023365021},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.38089999556541443},{"id":"https://openalex.org/C8505890","wikidata":"https://www.wikidata.org/wiki/Q605095","display_name":"Budget constraint","level":2,"score":0.3398999869823456},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.3375999927520752},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3082999885082245},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2915000021457672},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.25600001215934753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.29268","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29268","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.29268","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29268","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":{"LLM-guided":[0],"evolutionary":[1],"search":[2],"(Evolve":[3],"systems)":[4],"has":[5],"reached":[6],"state-of-the-art":[7],"results":[8],"on":[9,77,140],"mathematical":[10],"and":[11,25,43,60,80],"combinatorial":[12],"tasks,":[13,62],"yet":[14],"most":[15],"existing":[16],"systems":[17],"report":[18],"only":[19],"the":[20,27,50,54,115,127,137],"best":[21],"of":[22,37],"many":[23],"runs":[24],"leave":[26],"run-to-run":[28],"distribution":[29],"undocumented.":[30],"We":[31],"ask":[32],"how":[33,44],"a":[34,46,68,81,103,143],"fixed":[35],"budget":[36],"LLM":[38,108],"calls":[39,109],"should":[40],"be":[41],"allocated,":[42],"reliably":[45],"single":[47],"run":[48],"reaches":[49],"reported":[51],"numbers.":[52],"Sweeping":[53],"depth-breadth":[55,83],"grid":[56],"over":[57,126],"five":[58],"models":[59],"three":[61],"we":[63,98],"identify":[64],"two":[65],"empirical":[66],"regularities:":[67],"fitness-compute":[69],"envelope":[70],"along":[71],"which":[72],"capability":[73],"ordering":[74],"largely":[75],"collapses":[76],"effective":[78],"FLOPs,":[79],"bilinear":[82],"fit":[84],"with":[85,136],"task-specific":[86],"interaction;":[87],"both":[88],"are":[89],"gated":[90],"by":[91,95,124],"model-task":[92],"capability.":[93],"Motivated":[94],"these":[96],"regularities,":[97],"propose":[99],"BaSE":[100,120],"(Bandit-based":[101],"Self-Evolving),":[102],"multi-armed":[104],"bandit":[105],"that":[106],"allocates":[107],"across":[110,131],"parallel":[111],"trajectories.":[112],"Without":[113],"changing":[114],"model,":[116],"prompt,":[117],"or":[118],"evaluator,":[119],"improves":[121],"mean":[122],"fitness":[123],"12.3%":[125],"strongest":[128],"island-protocol":[129],"baseline":[130],"8":[132],"(model,":[133],"task)":[134],"cells,":[135],"largest":[138],"gains":[139],"high-variance":[141],"settings:":[142],"reliability":[144],"gain":[145],"from":[146],"allocation":[147],"alone.":[148]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-30T00:00:00"}
