ArBaWing Ar$ficial Bandits and...

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ArBaWingAr$ficialBanditsandWingmen

aprojectonFCASautonomyPe<erÖgren

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MessagesfromThisMorning

•  “Autonomyisacurrentpriority”–  AFRLCommanderMcMurry

•  “AkeytrendisAutoma4onandAutonomoussystems”–  SaabDirectorofFutureBusiness,LarsSjöström:

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Outline•  ProblemFormula$on– USAFPerspec$ve– Robust,Efficient,TransparentAutonomy– WhiteBoxvsBlackBoxAutonomy

•  Resultssofar•  FocusAhead

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ExampleResult

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ProblemFormula$on

•  FutureCombatAirSystem(FCAS):– MixofMannedandUnmannedsystems–  DistributedSensorsandWeapons–  FlexibleandAdap$ve

•  Needs:–  AutonomousDecisionMaking

•  Robust,Transparent,Efficient–  HumanAutonomyTeam

•  Robust,Transparent,Efficient

ArBaWingProjectGoals

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USAFPerspec$veUSAFVision:•  Human-AutonomyTeamsCri$calfactors:•  Robustness•  AutonomyLevels•  Easeofinterac$on•  Automa$ontransparency(i.e.Robust,Transparent,Efficient)

MicaEndsley

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WhyRobustandEfficientAutonomy?

•  WhyRobust?– Combatisunpredictable– Avoidbri<leautonomy(narrowassump$ons)

•  WhyEfficient?– Needtowincombat

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WhyTransparentAutonomy?

•  Operatorneedsto– KnowWhatsystemdoesandWhy– TrustSystem– StayintheLoop

•  RulesofEngagementàTransparency– Whydidyoufire?– Changesbetweenmissions

ApproachestoAI

•  BlackBoxExamples–  DeepLearning

•  State-of-the-Arton–  AlphaGo–  Objectrecogni$on–  OldAtarigames(several)

•  WhiteBoxExamples–  FiniteStateMachines–  Subsump$onArchitechture–  BehaviorTrees

•  State-of-the-Arton–  NewComputergames–  AirCombatSimula$on

Proposedsolu$on

•  DeepLearning–  Efficiency(extra)–  Needs30milliontrainingdatapoints•  fromWhiteboxdesign

•  BehaviorTrees–  Transparency–  Robustness–  Efficiency(State-of-Art)

•  and...–  RulesofEngagementcheck

–  Verifica$on/Valida$on–  Quickadapta$ontochange(Amraam->Meteor)

& Combina$on

AItool:BehaviorTrees

•  FromComputerGameAI•  Generalizesearlierapproaches–  FiniteStateMachines–  Subsump$onArchitecture–  Teleo-Reac$veApproach–  DecisionTrees

•  BTeditorsforMajorGameEngines:–  UnrealEngine–  Unity3D–  Pygame

•  Advantages– Modularity–  Flexibility–  Reuseability

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Resultssofar:Forma$ons

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Resultssofar:Combat1vs1

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Resultssofar:Combat2vs1

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Resultssofar:Combat2vs2

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Resultssofar:Patrolling

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Resultssofar

•  CoderunningdailyatFLSC(aircombatsim.center)

•  4pilotsvs4virtual– killsonbothsides– hardtotellwhoiswho

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FocusAheadforKTH/Saab

•  Inves$gateHuman-AutonomyTeams– CombineWhite/BlackBoxSolu$ons

– DifferentAutonomyLevels– Robustness,Efficiency,Transparency

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Organiza$on:KeyPartners•  Pe<erÖgren

–  AssociateProf.inRobo$csandAutonomousSyst,KTH–  9yearsatFOI,designingAirCombatbehaviorsatFLSC

•  HenriqueCostaMarques,PhD–  FormerBrazilianAirForcePilot–  ITAresearcherinAutonomousAirCombat

•  JoaoAlexandroB.M.Vilela–  FormerBrazilianAirForcePilotandflightinstructor–  AELBusinessDevelopmentmanager

•  LarsPääjärvi–  HeadofSensorFusionandTacLcalControl,SaabAeronau$cs

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Funding

•  ITA/AEL– 2MScstudentsduring2016– 2PhDstudentsstar$ng2017•  AELFundingfor1PhDstudentatITA

•  KTH/Saab– 1MScstudent2016– WillapplyforNFFP7project

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ThankYou...

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