CS347–IntroductiontoArtificialIntelligenceDr.
DanielTauritz(Dr.
T)DepartmentofComputerSciencetauritzd@mst.
eduhttp://web.
mst.
edu/~tauritzd/CS347coursewebsite:http://web.
mst.
edu/~tauritzd/courses/cs347/WhatisAISystemsthat…actlikehumans(TuringTest)thinklikehumansthinkrationallyactrationallyPlayUltimatumGameKeyhistoricaleventsforAI4thcenturyBCAristotlepropositionallogic1600'sDescartesmind-bodyconnection1805FirstprogrammablemachineMid1800'sCharlesBabbage's"differenceengine"&"analyticalengine"LadyLovelace'sObjection1847GeorgeBoolepropositionallogic1879GottlobFregepredicatelogicKeyhistoricaleventsforAI1931KurtGodel:IncompletenessTheoremInanylanguageexpressiveenoughtodescribenaturalnumberproperties,thereareundecidable(incomputable)truestatements1943McCulloch&Pitts:NeuralComputation1956Term"AI"coined1976Newell&Simon's"PhysicalSymbolSystemHypothesis"Aphysicalsymbolsystemhasthenecessaryandsufficientmeansforgeneralintelligentaction.
HowdifficultisittoachieveAIThreeSistersPuzzleRationalAgentsEnvironmentSensors(percepts)Actuators(actions)AgentFunctionAgentProgramPerformanceMeasuresRationalBehaviorDependson:Agent'sperformancemeasureAgent'spriorknowledgePossibleperceptsandactionsAgent'sperceptsequenceRationalAgentDefinition"Foreachpossibleperceptsequence,arationalagentselectsanactionthatisexpectedtomaximizeitsperformancemeasure,giventheevidenceprovidedbytheperceptsequenceandanypriorknowledgetheagenthas.
"TaskEnvironmentsPEASdescription&properties:Fully/PartiallyObservableDeterministic,Stochastic,StrategicEpisodic,SequentialStatic,Dynamic,Semi-dynamicDiscrete,ContinuousSingleagent,MultiagentCompetitive,CooperativeProblem-solvingagentsAdefinition:Problem-solvingagentsaregoalbasedagentsthatdecidewhattodobasedonanactionsequenceleadingtoagoalstate.
Problem-solvingstepsProblem-formulation(actions&states)Goal-formulation(states)Search(actionsequences)ExecutesolutionWell-definedproblemsInitialstateActionsetTransitionmodel:RESULT(s,a)GoaltestPathcostSolution/optimalsolutionExampleproblemsVacuumworldTic-tac-toe8-puzzle8-queensproblemSearchtreesRootcorrespondswithinitialstateVacuumstatespacevs.
searchtreeSearchalgorithmsiteratethroughgoaltestingandexpandingastateuntilgoalfoundOrderofstateexpansioniscritical!
Searchnodedatastructuren.
STATEn.
PARENT-NODEn.
ACTIONn.
PATH-COSTStatesareNOTsearchnodes!
FrontierFrontier=SetofleafnodesImplementedasaqueuewithops:EMPTY(queue)POP(queue)INSERT(element,queue)Queuetypes:FIFO,LIFO(stack),andpriorityqueueProblem-solvingperformanceCompletenessOptimalityTimecomplexitySpacecomplexityComplexityinAIb–branchingfactord–depthofshallowestgoalnodem–maxpathlengthinstatespaceTimecomplexity:#generatednodesSpacecomplexity:max#nodesstoredSearchcost:time+spacecomplexityTotalcost:search+pathcostTreeSearchBreadthFirstTreeSearch(BFTS)UniformCostTreeSearch(UCTS)Depth-FirstTreeSearch(DFTS)Depth-LimitedTreeSearch(DLTS)Iterative-DeepeningDepth-FirstTreeSearch(ID-DFTS)Examplestatespace#1BreadthFirstTreeSearch(BFTS)Frontier:FIFOqueueComplete:ifbanddarefiniteOptimal:ifpath-costisnon-decreasingfunctionofdepthTimecomplexity:O(b^d)Spacecomplexity:O(b^d)UniformCostTreeSearch(UCTS)Frontier:priorityqueueorderedbyg(n)DepthFirstTreeSearch(DFTS)Frontier:LIFOqueue(a.
k.
a.
stack)Complete:noOptimal:noTimecomplexity:O(bm)Spacecomplexity:O(bm)BacktrackingversionofDFTShasaspacecomplexityof:O(m)Depth-LimitedTreeSearch(DLTS)Frontier:LIFOqueue(a.
k.
a.
stack)Complete:notwhenl=βPruneiffail-lowforMin-playerPruneiffail-highforMax-playerDLMw/Alpha-BetaPruningTimeComplexityWorst-case:O(bd)Best-case:O(bd/2)[Knuth&Moore,1975]Average-case:O(b3d/4)MoveOrderingHeuristicsKnowledgebasedKillerMove:thelastmoveatagivendepththatcausedAB-pruningorhadbestminimaxvalueHistoryTableExamplegametreeExamplegametreeSearchDepthHeuristicsTimebased/StatebasedHorizonEffect:thephenomenonofdecidingonanon-optimalprincipalvariantbecauseanultimatelyunavoidabledamagingmoveseemstobeavoidedbyblockingittillpassedthesearchdepthSingularExtensions/QuiescenceSearchTimePerMoveConstantPercentageofremainingtimeStatedependentHybridQuiescenceSearchWhensearchdepthreached,computequiescencestateevaluationheuristicIfstatequiescent,thenproceedasusual;otherwiseincreasesearchdepthifquiescencesearchdepthnotyetreachedCallformat:QSDLM(root,depth,QSdepth),QSABDLM(root,depth,QSdepth,α,β),etc.
QSgametreeEx.
1QSgametreeEx.
2ForwardpruningBeamSearch(nbestmoves)ProbCut(forwardpruningversionofalpha-betapruning)TranspositionTables(1)HashtableofpreviouslycalculatedstateevaluationheuristicvaluesSpeedupisparticularlyhugeforiterativedeepeningsearchalgorithms!
GoodforchessbecauseoftenrepeatedstatesinsamesearchTranspositionTables(2)Datastructure:HashtableindexedbypositionElement:StateevaluationheuristicvalueSearchdepthofstoredvalueHashkeyofposition(toeliminatecollisions)(optional)BestmovefrompositionTranspositionTables(3)ZobristhashkeyGenerate3d-arrayofrandom64-bitnumbers(piecetype,locationandcolor)Startwitha64-bithashkeyinitializedto0Loopthroughcurrentposition,XOR'inghashkeywithZobristvalueofeachpiecefound(note:onceakeyhasbeenfound,useanincrementalapporachthatXOR'sthe"from"locationandthe"to"locationtomoveapiece)MTD(f)MTDf(root,guess,depth){lower=-∞;upper=∞;do{beta=guess+(guess==lower);guess=ABMaxV(root,depth,beta-1,beta);if(guessExtendedFutilityPruningRazoringState-SpaceSearchComplete-stateformulationObjectivefunctionGlobaloptimaLocaloptima(don'tusetextbook'sdefinition!
)Ridges,plateaus,andshouldersRandomsearchandlocalsearchSteepest-AscentHill-ClimbingGreedyAlgorithm-makeslocallyoptimalchoicesExample8queensproblemhas88≈17MstatesSAHCfindsglobaloptimumfor14%ofinstancesinonaverage4steps(3stepswhenstuck)SAHCw/upto100consecutivesidewaysmoves,findsglobaloptimumfor94%ofinstancesinonaverage21steps(64stepswhenstuck)StochasticHill-ClimbingChoosesatrandomfromamonguphillmovesProbabilityofselectioncanvarywiththesteepnessoftheuphillmoveOnaverageslowerconvergence,butalsolesschanceofprematureconvergenceMoreLocalSearchAlgorithmsFirst-choicehill-climbingRandom-restarthill-climbingSimulatedAnnealingPopulationBasedLocalSearchDeterministiclocalbeamsearchStochasticlocalbeamsearchEvolutionaryAlgorithmsParticleSwarmOptimizationAntColonyOptimizationParticleSwarmOptimizationPSOisastochasticpopulation-basedoptimizationtechniquewhichassignsvelocitiestopopulationmembersencodingtrialsolutionsPSOupdaterules:PSOdemo:http://www.
borgelt.
net//psopt.
htmlAntColonyOptimizationPopulationbasedPheromonetrailandstigmergeticcommunicationShortestpathsearchingStochasticmovesOnlineSearchOfflinesearchvs.
onlinesearchInterleavingcomputation&actionExplorationproblems,safelyexplorableAgentshaveaccessto:ACTIONS(s)c(s,a,s')GOAL-TEST(s)OnlineSearchOptimalityCR–CompetitiveRatioTAPC–TotalActualPathCostC*-OptimalPathCostBestcase:CR=1Worstcase:CR=∞OnlineSearchAlgorithmsOnline-DFS-AgentRandomWalkLearningReal-TimeA*(LRTA*)OnlineSearchExampleGraph1OnlineSearchExampleGraph2OnlineSearchExampleGraph3AIcoursesatS&TCS345ComputationalRoboticManipulation(SP2012)CS347IntroductiontoArtificialIntelligence(SP2012)CS348EvolutionaryComputing(FS2011)CS434DataMining&KnowledgeDiscovery(FS2011)CS447AdvancedTopicsinAI(SP2013)CS448AdvancedEvolutionaryComputing(SP2012)CpE358ComputationalIntelligence(FS2011)SysEng378IntrotoNeuralNetworks&Applications
无忧云怎么样?无忧云,无忧云是一家成立于2017年的老牌商家旗下的服务器销售品牌,现由深圳市云上无忧网络科技有限公司运营,是正规持证IDC/ISP/IRCS商家,主要销售国内、中国香港、国外服务器产品,线路有腾讯云国外线路、自营香港CN2线路等,都是中国大陆直连线路,非常适合免备案建站业务需求和各种负载较高的项目,同时国内服务器也有多个BGP以及高防节点。一、无忧云官网点击此处进入无忧云官方网站二...
TMThosting发布了今年黑色星期五的促销活动,即日起到12月6日,VPS主机最低55折起,独立服务器9折起,开设在西雅图机房。这是一家成立于2018年的国外主机商,主要提供VPS和独立服务器租用业务,数据中心包括美国西雅图和达拉斯,其中VPS基于KVM架构,都有提供免费的DDoS保护,支持选择Windows或者Linux操作系统。Budget HDD系列架构CPU内存硬盘流量系统价格单核51...
华纳云(HNCloud Limited)是一家专业的全球数据中心基础服务提供商,总部在香港,隶属于香港联合通讯国际有限公司,拥有香港政府颁发的商业登记证明,保证用户的安全性和合规性。 华纳云是APNIC 和 ARIN 会员单位。主要提供数据中心基础服务、互联网业务解决方案, 以及香港服务器租用、香港服务器托管、香港云服务器、美国云服务器,云计算、云安全技术研发等产品和服务。其中云服务器基于成熟的 ...
graphsearch为你推荐
更新win7支持ipad支持ipadipad连不上wifiipad无法加入网络怎么回事iphone连不上wifi苹果8p连接不了WiFi127.0.0.1DNS老是被修改为127.0.0.1,这是为什么?联通版iphone4s怎样看苹果4S是联通版还是电信版csshack怎样找css hack 的最新使用方法google分析google analysis干什么用的?联通合约机iphone5iphone5联通合约机是怎么回事
免费申请网站域名 主机测评网 樊云 la域名 vmsnap3 好看的留言 parseerror 双拼域名 空间论坛 秒杀预告 isp服务商 福建铁通 Updog 申请免费空间和域名 中国linux php服务器 服务器防火墙 贵阳电信 酸酸乳 徐州电信 更多