{"id":"https://openalex.org/W4411600152","doi":"https://doi.org/10.1109/cec65147.2025.11043114","title":"Progressive Surrogate Modeling for a Multi-objective Competitive Co-evolutionary (MoCCoEv) Wargame Strategy Optimization","display_name":"Progressive Surrogate Modeling for a Multi-objective Competitive Co-evolutionary (MoCCoEv) Wargame Strategy Optimization","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4411600152","doi":"https://doi.org/10.1109/cec65147.2025.11043114"},"language":"en","primary_location":{"id":"doi:10.1109/cec65147.2025.11043114","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec65147.2025.11043114","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049905796","display_name":"Ritam Guha","orcid":"https://orcid.org/0000-0002-1375-777X"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ritam Guha","raw_affiliation_strings":["Michigan State University,East Lansing,MI,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University,East Lansing,MI,USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077795414","display_name":"Ryan Mckendrick","orcid":null},"institutions":[{"id":"https://openalex.org/I2948394018","display_name":"Northrop Grumman (United States)","ror":"https://ror.org/05kewds18","country_code":"US","type":"company","lineage":["https://openalex.org/I2948394018"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ryan Mckendrick","raw_affiliation_strings":["Northrop Grumman Corporation,Falls Church,VA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northrop Grumman Corporation,Falls Church,VA,USA","institution_ids":["https://openalex.org/I2948394018"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046755175","display_name":"Bradley Feest","orcid":null},"institutions":[{"id":"https://openalex.org/I2948394018","display_name":"Northrop Grumman (United States)","ror":"https://ror.org/05kewds18","country_code":"US","type":"company","lineage":["https://openalex.org/I2948394018"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bradley Feest","raw_affiliation_strings":["Northrop Grumman Corporation,Falls Church,VA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northrop Grumman Corporation,Falls Church,VA,USA","institution_ids":["https://openalex.org/I2948394018"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088394271","display_name":"Kalyanmoy Deb","orcid":"https://orcid.org/0000-0001-7402-9939"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kalyanmoy Deb","raw_affiliation_strings":["Michigan State University,East Lansing,MI,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University,East Lansing,MI,USA","institution_ids":["https://openalex.org/I87216513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15432977,"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":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.9538999795913696,"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"}},"topics":[{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.9538999795913696,"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/T11741","display_name":"Flexible and Reconfigurable Manufacturing Systems","score":0.9501000046730042,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/surrogate-model","display_name":"Surrogate model","score":0.705964982509613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6148381233215332},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.46468523144721985},{"id":"https://openalex.org/keywords/evolutionary-computation","display_name":"Evolutionary computation","score":0.447131872177124},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40503180027008057},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19726243615150452}],"concepts":[{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.705964982509613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6148381233215332},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.46468523144721985},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.447131872177124},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40503180027008057},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19726243615150452}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec65147.2025.11043114","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec65147.2025.11043114","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320308204","display_name":"Northrop Grumman","ror":"https://ror.org/05kewds18"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1515037263","https://openalex.org/W1967989271","https://openalex.org/W2096626693","https://openalex.org/W2108587684","https://openalex.org/W2135046866","https://openalex.org/W2143299520","https://openalex.org/W2288585628","https://openalex.org/W2296218809","https://openalex.org/W2557596507","https://openalex.org/W2622041536","https://openalex.org/W4296129757","https://openalex.org/W4400496388","https://openalex.org/W4402289119"],"related_works":["https://openalex.org/W4297582752","https://openalex.org/W4285805405","https://openalex.org/W2391924736","https://openalex.org/W3133779647","https://openalex.org/W4293363729","https://openalex.org/W1560122427","https://openalex.org/W3041827036","https://openalex.org/W1993493607","https://openalex.org/W2021957875","https://openalex.org/W2802808995"],"abstract_inverted_index":{"Wargame":[0],"strategy":[1,66],"optimization":[2,43,67,137],"involves":[3],"two":[4],"competing":[5],"agents\u2014offense":[6],"and":[7,110,135],"defense\u2014and":[8],"requires":[9],"extensive":[10],"simulations":[11],"of":[12,59,128],"wargame":[13,65,93],"tools,":[14],"resulting":[15],"in":[16,104,125],"high":[17],"computational":[18],"costs":[19],"for":[20,51],"evaluating":[21],"potential":[22],"strategies.":[23,97],"To":[24],"reduce":[25],"these":[26],"costs,":[27],"surrogate":[28,53,60,82,113],"models":[29,61,121],"are":[30,101,122],"employed":[31],"to":[32,55,91,108,131],"approximate":[33],"the":[34,42,57,64,81,105,112,120,126],"objective":[35],"functions,":[36],"with":[37],"their":[38],"accuracy":[39],"directly":[40],"affecting":[41],"process.":[44],"This":[45,115],"paper":[46],"proposes":[47],"a":[48,72],"novel":[49],"framework":[50],"progressive":[52],"modeling":[54],"improve":[56,111],"quality":[58],"while":[62],"addressing":[63],"problem.":[68],"Our":[69],"approach":[70],"utilizes":[71],"Multi-objective":[73],"Competitive":[74],"Co-Evolutionary":[75],"(MoCCoEv)":[76],"algorithm,":[77],"which":[78],"iteratively":[79],"refines":[80],"models.":[83,114],"The":[84,98],"process":[85,117],"begins":[86],"by":[87],"using":[88],"MoCCoEv":[89],"algorithm":[90],"optimize":[92],"strategies":[94,100],"generating":[95],"new":[96,99],"then":[102],"replaced":[103],"training":[106],"data":[107],"update":[109],"cyclical":[116],"ensures":[118],"that":[119],"continuously":[123],"refined":[124],"regions":[127],"interest,":[129],"leading":[130],"more":[132],"accurate":[133],"predictions":[134],"enhanced":[136],"results.":[138]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
