{"id":"https://openalex.org/W7125920205","doi":"https://doi.org/10.1177/09266801251412545","title":"An interpretable machine learning framework for modeling and analysis of\u00a0swarm robot behaviors","display_name":"An interpretable machine learning framework for modeling and analysis of\u00a0swarm robot behaviors","publication_year":2026,"publication_date":"2026-01-28","ids":{"openalex":"https://openalex.org/W7125920205","doi":"https://doi.org/10.1177/09266801251412545"},"language":"en","primary_location":{"id":"doi:10.1177/09266801251412545","is_oa":false,"landing_page_url":"https://doi.org/10.1177/09266801251412545","pdf_url":null,"source":{"id":"https://openalex.org/S133922704","display_name":"Journal of High Speed Networks","issn_l":"0926-6801","issn":["0926-6801","1875-8940"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of High Speed Networks","raw_type":"journal-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/A5107707730","display_name":"Mohammed Al-Hubaishi","orcid":null},"institutions":[{"id":"https://openalex.org/I25010766","display_name":"Hali\u00e7 University","ror":"https://ror.org/022xhck05","country_code":"TR","type":"education","lineage":["https://openalex.org/I25010766"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Mohammed Al-Hubaishi","raw_affiliation_strings":["Hali\u00e7 University"],"raw_orcid":"https://orcid.org/0000-0002-9940-3592","affiliations":[{"raw_affiliation_string":"Hali\u00e7 University","institution_ids":["https://openalex.org/I25010766"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5118648010","display_name":"Wail Zita","orcid":null},"institutions":[{"id":"https://openalex.org/I25010766","display_name":"Hali\u00e7 University","ror":"https://ror.org/022xhck05","country_code":"TR","type":"education","lineage":["https://openalex.org/I25010766"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Wail Zita","raw_affiliation_strings":["Department of Software Engineering, Faculty of Engineering, Hali\u00e7 University, Istanbul, T\u00fcrkiye"],"raw_orcid":"https://orcid.org/0009-0007-0744-7795","affiliations":[{"raw_affiliation_string":"Department of Software Engineering, Faculty of Engineering, Hali\u00e7 University, Istanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I25010766"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5107707730"],"corresponding_institution_ids":["https://openalex.org/I25010766"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07749693,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"32","issue":"2","first_page":"107","last_page":"125"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.39399999380111694,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.39399999380111694,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12321","display_name":"Insect Pheromone Research and Control","score":0.33809998631477356,"subfield":{"id":"https://openalex.org/subfields/1109","display_name":"Insect Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.023099999874830246,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/classifier","display_name":"Classifier (UML)","score":0.6456000208854675},{"id":"https://openalex.org/keywords/swarm-robotics","display_name":"Swarm robotics","score":0.6448000073432922},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6046000123023987},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.515500009059906},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5029000043869019},{"id":"https://openalex.org/keywords/swarm-behaviour","display_name":"Swarm behaviour","score":0.5019999742507935},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.45649999380111694},{"id":"https://openalex.org/keywords/cohesion","display_name":"Cohesion (chemistry)","score":0.42730000615119934},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.41110000014305115}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.803600013256073},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7851999998092651},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6651999950408936},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6456000208854675},{"id":"https://openalex.org/C169337768","wikidata":"https://www.wikidata.org/wiki/Q2446723","display_name":"Swarm robotics","level":3,"score":0.6448000073432922},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6046000123023987},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.515500009059906},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5029000043869019},{"id":"https://openalex.org/C181335050","wikidata":"https://www.wikidata.org/wiki/Q14915018","display_name":"Swarm behaviour","level":2,"score":0.5019999742507935},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.45649999380111694},{"id":"https://openalex.org/C104054115","wikidata":"https://www.wikidata.org/wiki/Q216828","display_name":"Cohesion (chemistry)","level":2,"score":0.42730000615119934},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.41110000014305115},{"id":"https://openalex.org/C58103923","wikidata":"https://www.wikidata.org/wiki/Q2286025","display_name":"Silhouette","level":2,"score":0.3709999918937683},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.37040001153945923},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3675000071525574},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.359499990940094},{"id":"https://openalex.org/C40651066","wikidata":"https://www.wikidata.org/wiki/Q5048220","display_name":"Cascading classifiers","level":4,"score":0.3441999852657318},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.320499986410141},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C207968372","wikidata":"https://www.wikidata.org/wiki/Q310401","display_name":"k-means clustering","level":3,"score":0.2849000096321106},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2806999981403351},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.28040000796318054},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2711000144481659},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2590999901294708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/09266801251412545","is_oa":false,"landing_page_url":"https://doi.org/10.1177/09266801251412545","pdf_url":null,"source":{"id":"https://openalex.org/S133922704","display_name":"Journal of High Speed Networks","issn_l":"0926-6801","issn":["0926-6801","1875-8940"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of High Speed Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7738305330276489,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2118331730","https://openalex.org/W2760361646","https://openalex.org/W2948393160","https://openalex.org/W2972866190","https://openalex.org/W3003752967","https://openalex.org/W3005838681","https://openalex.org/W3012474544","https://openalex.org/W3014630000","https://openalex.org/W3176202740","https://openalex.org/W3205022715","https://openalex.org/W4296366012","https://openalex.org/W4311443434","https://openalex.org/W4321015392","https://openalex.org/W4365517024","https://openalex.org/W4366828030","https://openalex.org/W4384563452","https://openalex.org/W4402783918","https://openalex.org/W4406924570","https://openalex.org/W4408223351","https://openalex.org/W4409076728","https://openalex.org/W4409992136","https://openalex.org/W4413180376","https://openalex.org/W4415481402"],"related_works":[],"abstract_inverted_index":{"Swarm":[0],"robotics":[1,51],"aims":[2],"to":[3,83,143,164],"achieve":[4],"robust":[5],"collective":[6],"behaviors":[7,42],"through":[8],"large":[9],"numbers":[10],"of":[11,49,67,135,212],"relatively":[12],"simple":[13],"robots,":[14,54],"but":[15],"modeling":[16,37],"and":[17,38,58,75,77,91,100,104,109,117,128,137,180,191,206,222,224],"interpreting":[18],"these":[19],"emergent":[20],"dynamics":[21],"from":[22],"real":[23,184],"experimental":[24],"data":[25,186],"remains":[26],"challenging.":[27],"This":[28],"work":[29],"proposes":[30],"an":[31,138],"interpretable":[32,181],"machine":[33],"learning":[34],"framework":[35,175],"for":[36,183,215],"analyzing":[39],"swarm":[40,50,213],"robot":[41],"using":[43],"a":[44,64,79,132,177],"public":[45],"IEEE":[46],"DataPort":[47],"dataset":[48],"experiments":[52],"(eight":[53],"200":[55],"time":[56],"steps,":[57],"1,600":[59],"labeled":[60,153],"samples).":[61],"We":[62],"construct":[63],"feature-based":[65],"representation":[66],"local":[68,161],"interaction":[69,162],"metrics":[70],"(alignment,":[71],"cohesion,":[72],"separation,":[73],"velocity,":[74],"position)":[76],"train":[78],"Random":[80,156],"Forest":[81,157],"classifier":[82,95],"recognize":[84],"four":[85],"behavioral":[86,122],"phases:":[87],"exploration,":[88],"aggregation,":[89],"formation,":[90],"foraging.":[92],"The":[93,193],"proposed":[94],"attains":[96],"98.12%":[97],"overall":[98],"accuracy":[99],"high":[101,169],"per-class":[102],"precision":[103,219],"recall,":[105],"while":[106],"feature":[107],"importance":[108],"Shapley":[110],"additive":[111],"explanation":[112],"analyses":[113],"highlight":[114],"alignment":[115],"(31.44%)":[116],"cohesion":[118],"(21.62%)":[119],"as":[120,218],"dominant":[121],"drivers.":[123],"Unsupervised":[124],"clustering":[125],"with":[126,151],"KMeans":[127],"DBSCAN,":[129],"supported":[130],"by":[131],"Silhouette":[133],"score":[134],"0.2541":[136],"adjusted":[139],"Rand":[140],"index":[141],"up":[142],"0.69,":[144],"reveals":[145],"moderately":[146],"separable":[147],"latent":[148],"structure":[149],"consistent":[150],"the":[152],"phases.":[154],"A":[155],"regressor":[158],"further":[159],"links":[160],"features":[163,199],"global":[165],"performance":[166,207],"indicators,":[167],"achieving":[168],"results":[170,194],"on":[171],"task-level":[172],"outcomes.":[173],"Our":[174],"provides":[176],"unified,":[178],"reproducible,":[179],"pipeline":[182],"multi-robot":[185],"that":[187,196],"combines":[188],"classification,":[189],"clustering,":[190],"regression.":[192],"demonstrate":[195],"biologically":[197],"inspired":[198],"can":[200],"support":[201],"accurate,":[202],"explainable":[203],"phase":[204],"recognition":[205],"prediction,":[208],"enabling":[209],"data-driven":[210],"design":[211],"controllers":[214],"applications":[216],"such":[217],"agriculture,":[220],"search":[221],"rescue,":[223],"environmental":[225],"monitoring.":[226]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-01-29T00:00:00"}