{"id":"https://openalex.org/W2108210027","doi":"https://doi.org/10.1109/acc.2015.7171820","title":"Optimal remote estimation over Action Dependent Switching Channels: Managing workload and bias of a human operator","display_name":"Optimal remote estimation over Action Dependent Switching Channels: Managing workload and bias of a human operator","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W2108210027","doi":"https://doi.org/10.1109/acc.2015.7171820","mag":"2108210027"},"language":"en","primary_location":{"id":"doi:10.1109/acc.2015.7171820","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acc.2015.7171820","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 American Control Conference (ACC)","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/A5074486100","display_name":"David Ward","orcid":"https://orcid.org/0000-0001-5476-9526"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"David Ward","raw_affiliation_strings":["The Department of Electrical and Computer Engineering, University of Maryland, College Park","[Department of Electrical and Computer Engineering, University of Maryland College Park, USA]"],"affiliations":[{"raw_affiliation_string":"The Department of Electrical and Computer Engineering, University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"[Department of Electrical and Computer Engineering, University of Maryland College Park, USA]","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065643877","display_name":"Nuno C. Martins","orcid":"https://orcid.org/0000-0003-2083-8102"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nuno Martins","raw_affiliation_strings":["The Department of Electrical and Computer Engineering, University of Maryland, College Park","[Department of Electrical and Computer Engineering, University of Maryland College Park, USA]"],"affiliations":[{"raw_affiliation_string":"The Department of Electrical and Computer Engineering, University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"[Department of Electrical and Computer Engineering, University of Maryland College Park, USA]","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053858045","display_name":"Brian M. Sadler","orcid":"https://orcid.org/0000-0002-9564-3812"},"institutions":[{"id":"https://openalex.org/I166416128","display_name":"DEVCOM Army Research Laboratory","ror":"https://ror.org/011hc8f90","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I166416128","https://openalex.org/I2802705668","https://openalex.org/I4210154437"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian M. Sadler","raw_affiliation_strings":["The Army Research Laboratory","Army Research Laboratory, USA"],"affiliations":[{"raw_affiliation_string":"The Army Research Laboratory","institution_ids":["https://openalex.org/I166416128"]},{"raw_affiliation_string":"Army Research Laboratory, USA","institution_ids":["https://openalex.org/I166416128"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074486100"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":0.4839,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.64273441,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"abs 1110 3564","issue":null,"first_page":"3168","last_page":"3174"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9855999946594238,"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/T13553","display_name":"Age of Information Optimization","score":0.9793999791145325,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6879922151565552},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6443759202957153},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6146987080574036},{"id":"https://openalex.org/keywords/crossover","display_name":"Crossover","score":0.5359943509101868},{"id":"https://openalex.org/keywords/binary-symmetric-channel","display_name":"Binary symmetric channel","score":0.5249930620193481},{"id":"https://openalex.org/keywords/precoding","display_name":"Precoding","score":0.4752782881259918},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.468727707862854},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.4435203969478607},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.42121535539627075},{"id":"https://openalex.org/keywords/finite-state-machine","display_name":"Finite-state machine","score":0.4200449585914612},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36575329303741455},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24255117774009705},{"id":"https://openalex.org/keywords/channel-capacity","display_name":"Channel capacity","score":0.23841944336891174},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.20414674282073975},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.1928650140762329},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1149272620677948}],"concepts":[{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6879922151565552},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6443759202957153},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6146987080574036},{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.5359943509101868},{"id":"https://openalex.org/C173988684","wikidata":"https://www.wikidata.org/wiki/Q863510","display_name":"Binary symmetric channel","level":4,"score":0.5249930620193481},{"id":"https://openalex.org/C160562895","wikidata":"https://www.wikidata.org/wiki/Q7239557","display_name":"Precoding","level":4,"score":0.4752782881259918},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.468727707862854},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.4435203969478607},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.42121535539627075},{"id":"https://openalex.org/C167822520","wikidata":"https://www.wikidata.org/wiki/Q176452","display_name":"Finite-state machine","level":2,"score":0.4200449585914612},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36575329303741455},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24255117774009705},{"id":"https://openalex.org/C97744766","wikidata":"https://www.wikidata.org/wiki/Q870845","display_name":"Channel capacity","level":3,"score":0.23841944336891174},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.20414674282073975},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.1928650140762329},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1149272620677948},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acc.2015.7171820","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acc.2015.7171820","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 American Control Conference (ACC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1995323028","https://openalex.org/W2062626064","https://openalex.org/W2099111195","https://openalex.org/W2107564936","https://openalex.org/W2136817255","https://openalex.org/W2147356386","https://openalex.org/W2165805053","https://openalex.org/W2404625266","https://openalex.org/W2478708596","https://openalex.org/W2951077615","https://openalex.org/W2989448192","https://openalex.org/W4299379997","https://openalex.org/W6676100626","https://openalex.org/W6684110770","https://openalex.org/W6713593790"],"related_works":["https://openalex.org/W4281688526","https://openalex.org/W2152088989","https://openalex.org/W2756419127","https://openalex.org/W4366493479","https://openalex.org/W2401571617","https://openalex.org/W2347477706","https://openalex.org/W2905893439","https://openalex.org/W3135374966","https://openalex.org/W4299389082","https://openalex.org/W2953205382"],"abstract_inverted_index":{"Consider":[0],"a":[1,7,14,28,46,146,170,196,216,237,265],"remote":[2],"estimation":[3],"system":[4],"formed":[5],"by":[6,70,275],"channel":[8,26,49,53,63,127,155,213,263],"and":[9,108,114,221,242,271,277],"an":[10,110],"encoder":[11,60,115,241],"that":[12,116,131,149,184],"assesses":[13],"continuous":[15],"random":[16],"variable":[17],"denoted":[18,80],"as":[19,81,195,215],"source.":[20],"The":[21],"internal":[22],"structure":[23],"of":[24,41,77,99,121,172,189,200,218,255],"the":[25,36,42,59,62,67,71,93,97,100,118,122,126,140,143,154,164,167,185,206,233,239,253,262],"has":[27],"finite":[29],"state":[30,34,40],"machine":[31],"(FSM)":[32],"whose":[33,269],"dictates":[35],"transmission":[37],"characteristics.":[38],"Each":[39],"FSM":[43,73,144,168,207],"corresponds":[44],"to":[45,61,66,106,142,211,258],"discrete":[47],"memoryless":[48],"(DMC).":[50],"At":[51],"each":[52],"use,":[54],"information":[55],"is":[56,79,145,208,236],"transmitted":[57],"from":[58],"output":[64,95],"according":[65],"DMC":[68,235],"selected":[69],"current":[72,276],"state.":[74],"This":[75,102],"class":[76],"channels":[78],"Action":[82],"Dependent":[83],"Switching":[84],"Channel,":[85],"or":[86],"ADS.":[87],"An":[88],"action":[89,111,135,243],"feedback":[90,112,136,244],"policy":[91,113],"maps":[92],"channel's":[94],"into":[96],"input":[98,141],"FSM.":[101],"paper":[103],"investigates":[104],"methods":[105],"analyze":[107],"design":[109],"minimize":[117],"differential":[119],"entropy":[120],"source":[123],"conditioned":[124],"on":[125,153],"output.":[128,156],"We":[129,157,250],"show":[130],"there":[132,228],"are":[133,193,229,273],"optimal":[134,240],"policies":[137,245],"for":[138,163,225],"which":[139,192,261],"deterministic":[147],"sequence":[148],"does":[150],"not":[151],"depend":[152],"also":[158,209,223,251],"provide":[159],"additional":[160],"structural":[161],"results":[162],"case":[165],"when":[166,227],"parametrizes":[169],"set":[171],"Binary":[173],"Symmetric":[174],"Channels":[175],"(BSC)":[176],"with":[177],"differing":[178],"crossover":[179,198],"probabilities.":[180],"Here,":[181],"we":[182],"consider":[183],"ADS":[186],"contains":[187],"states":[188],"no":[190,230],"transmission,":[191],"modeled":[194],"BSC":[197],"probability":[199],"one":[201],"half.":[202],"In":[203],"this":[204,256],"case,":[205],"used":[210],"model":[212,257],"degradation":[214],"result":[217],"multiple":[219],"transmissions,":[220],"it":[222],"allows":[224],"recovery":[226],"transmissions.":[231],"When":[232],"switching":[234],"BSC,":[238],"can":[246],"be":[247],"computed":[248],"separately.":[249],"discuss":[252],"relevance":[254],"applications":[259],"in":[260],"represents":[264],"human":[266],"decision":[267],"maker":[268],"reliability":[270],"bias":[272],"affected":[274],"past":[278],"outputs.":[279]},"counts_by_year":[{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
