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Algorithm for reinforcement learning

Algorithm for reinforcement learning

ID：40378596

大小：1.88 MB

页数：98页

时间：2019-08-01

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1、AlgorithmsforReinforcementLearningDraftofthelecturepublishedintheSynthesisLecturesonArti cialIntelligenceandMachineLearningseriesbyMorgan&ClaypoolPublishersCsabaSzepesvariJune9,2009Contents1Overview32Markovdecisionprocesses72.1Preliminaries...................................72.2MarkovDecisionPro

2、cesses............................82.3Valuefunctions..................................122.4DynamicprogrammingalgorithmsforsolvingMDPs..............163Valuepredictionproblems173.1Temporaldi erencelearningin nitestatespaces...............183.1.1TabularTD(0)..............................183.1.2Every-

3、visitMonte-Carlo.........................213.1.3TD():UnifyingMonte-CarloandTD(0)................233.2Algorithmsforlargestatespaces........................253.2.1TD()withfunctionapproximation...................293.2.2Gradienttemporaldi erencelearning..................333.2.3Least-squaresmethods..

4、........................36Lastupdate:August18,201013.2.4Thechoiceofthefunctionspace.....................424Control454.1Acatalogoflearningproblems..........................454.2Closed-loopinteractivelearning.........................474.2.1Onlinelearninginbandits........................474.2.2Activ

5、elearninginbandits........................494.2.3ActivelearninginMarkovDecisionProcesses.............504.2.4OnlinelearninginMarkovDecisionProcesses.............514.3Directmethods..................................564.3.1Q-learningin niteMDPs........................564.3.2Q-learningwithfunctionappro

6、ximation................594.4Actor-criticmethods...............................624.4.1Implementingacritic...........................644.4.2Implementinganactor..........................655Forfurtherexploration725.1Furtherreading..................................725.2Applications....................

7、................735.3Software......................................735.4Acknowledgements................................73AThetheoryofdiscountedMarkoviandecisionprocesses74A.1ContractionsandBanach's xed-pointtheo

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