├── Challenges ├── BrakingDAG.JPG ├── Breaking.ipynb ├── BreakingData.csv ├── ChallengeWeekend.pdf ├── CliffWalking.ipynb ├── CliffWalkingDiagram.JPG └── GeneralPolicyInterationDIagram.pdf ├── Homework ├── FiguresHW6.pptx ├── GSPC_Yahoo_Oct_8_19.csv ├── GridWorldFactory.JPG ├── Homework1.ipynb ├── Homework2.ipynb ├── Homework3.ipynb ├── Homework4.ipynb ├── Homework5.ipynb ├── Homework6.ipynb ├── Homework7.ipynb ├── Homework8.ipynb ├── Influence.jpg ├── InfluenceSample.JPG ├── MurderDirected.JPG └── OptimalPlansOnGridWorld.JPG ├── Lesson0_Introduction_Probability ├── IntroductionToProbabalisticProgramming.ipynb ├── Review_of_Probability.ipynb └── img │ ├── AIModel.JPG │ └── AgentModel.JPG ├── Lesson1_Bayes_Networks ├── 1_DirectedGraphicalModels.pdf ├── 1_Introduction.pdf ├── IntroductionToBayesNetworks.ipynb └── img │ ├── BayesBall.JPG │ ├── Dependency.JPG │ ├── GraphTypes.JPG │ ├── Independencies2.JPG │ ├── LetterDAG.JPG │ └── Representation.JPG ├── Lesson2_MarkovNetworks ├── 2_MarkovGraphs.pdf ├── IntroductionToMarkovNetworks.ipynb └── img │ ├── Cliques1.JPG │ ├── Cliques2.JPG │ ├── DAGvsMN.JPG │ ├── Diagrams.pptx │ ├── LetterCliques.JPG │ ├── LetterDAG.JPG │ ├── MarkovBlanket.JPG │ ├── MoralizedGraph.JPG │ ├── MoralizedLetter.JPG │ ├── NoDAG.JPG │ ├── Representation.JPG │ └── Separation.JPG ├── Lesson3_ExactInference ├── 3_ExactInference.pdf ├── ExactInferenceMethods.ipynb └── img │ ├── Chain1.JPG │ ├── CliqueTree.JPG │ ├── Collect.JPG │ ├── DAGFactor.JPG │ ├── Distribute.JPG │ ├── Eliminate1.JPG │ ├── Eliminate2.JPG │ ├── Eliminate3.JPG │ ├── Eliminate4.JPG │ ├── EliminationTree.JPG │ ├── FactorToVar.JPG │ ├── FourCycle.JPG │ ├── Inference.JPG │ ├── LetterDAG.JPG │ ├── Loopy.JPG │ ├── MarkovBlanket.JPG │ ├── MarkovFactor.JPG │ ├── Moralized.JPG │ ├── MultiConnected.JPG │ ├── MultiConnectedMoralized.JPG │ ├── StudentGraph.JPG │ ├── SumProductTree.JPG │ ├── Triangle1.JPG │ ├── Triangle2.JPG │ ├── Triangulated.JPG │ ├── Undirected1.JPG │ └── VarToFactor.JPG ├── Lesson4_Learning ├── 4_LearningInGraphicalModels.pdf ├── IntroductionToLearningModelParameters.ipynb └── img │ ├── Factorizing.JPG │ ├── Learning.JPG │ ├── LetterDAG.JPG │ └── PlateDiagram.JPG ├── Lesson5_Learning_Part2 ├── IntroductiontoLearningModelStructure.ipynb ├── StudentSimulation.py └── img │ ├── FullyConneted.JPG │ ├── Learning.JPG │ └── LetterDAG.JPG ├── Lesson6_Utility_and_Decision_Trees ├── 6_DecisionsUnderUncertainty.pdf ├── IntroductionToUtilityDecisionTrees.ipynb └── img │ ├── AgentEnvironment.JPG │ ├── Bridge.JPG │ ├── RandomVariable.JPG │ └── Utility.JPG ├── Lesson7_MarkovDecisionProcesses ├── 7_MarkovProcesses.pdf ├── IntroductionToMarkovDecisionProcesses.ipynb ├── IntroductionToRL.pdf ├── MarkovDecisionProcesses.pdf └── img │ ├── AgentEnvironment.JPG │ ├── CarRewards.JPG │ └── CarStates.JPG ├── Lesson8_LVM_Variational ├── 8_LatentVariable_VariationalMethods.pdf └── Introduction_LVM_Variational.ipynb ├── Lesson9_IntroductionToDynamicProgramming ├── 9_IntroToDynamicProgramming.pdf ├── Introduction_To_Dynamic_Programming.ipynb └── img │ ├── ActionValueBackup.JPG │ ├── Backups.JPG │ ├── DPAgent.JPG │ ├── GPI.JPG │ ├── GridWorld.JPG │ ├── OptimalPath.JPG │ └── ValueBackup.JPG ├── Lesson_10_Bandit_Problems ├── 10_Bandits.pdf ├── 10_IntroductionToRL.pdf ├── Introduction_to_Bandit_Problems.ipynb └── img │ ├── BanditAgent.JPG │ ├── OneArmedBandit.jpg │ └── multiarmedbandit.jpg ├── Lesson_11_MonteCarloReinforcementLearning ├── 11_MC_RL.pdf ├── IntroToMonteCarloReinforcementLearning.ipynb └── img │ ├── GPI.JPG │ ├── GridWorld.JPG │ ├── MC_Backup.JPG │ └── RL_AgentModel.JPG ├── Lesson_12_TDandQLearning ├── 12_TD_Q_Learning.pdf ├── IntroductionToQLearning.ipynb ├── IntroductionToTDLearning.ipynb └── img │ ├── GridWorld.JPG │ ├── Q-Learning.JPG │ ├── RL_AgentModel.JPG │ ├── SARSA.JPG │ ├── SARSAN.JPG │ ├── TD0.JPG │ └── TDN.JPG ├── Lesson_13_DeepFunctionApproximation ├── 13_OverviewOfDL.pdf ├── GettingStartedKeras.ipynb ├── IntrotoDeepFunctionApproximation.ipynb └── img │ ├── Accuracy-Layers.JPG │ ├── Accuracy-Parameters.JPG │ ├── CompGraph1.JPG │ ├── CompGraph2.JPG │ ├── Hidden.JPG │ ├── L2.jpg │ ├── Lesson1Figures.pptx │ ├── LinearNetwork.JPG │ ├── LossGraph.JPG │ ├── MachineIntelligence.JPG │ ├── Preceptron.JPG │ ├── SVD.png │ └── Tikhonov_board.jpg ├── Lesson_14_FunctionApproximation ├── 14_FunctionAppoxForRL.pdf ├── DeepQLearning.ipynb ├── IntroToFunctionApproximationForRL.ipynb └── img │ ├── AgentEnvironment.JPG │ ├── DQN.JPG │ ├── ReplayBuffer.JPG │ ├── Tile1.JPG │ └── Tile2.JPG ├── Lesson_15_PolicyGradient ├── 15_PolicyGradient.pdf └── IntroductionToPolicyGradients.ipynb ├── Models ├── insurance.bif └── mildew.bif └── README.md /Challenges/BrakingDAG.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/StephenElston/CSCI_E_82A_Probabalistic_Programming/HEAD/Challenges/BrakingDAG.JPG 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