Exam 1: Algorithms and Logic in Probabilistic Reasoning and Planning

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Where does the Hidden Markov Model is used?

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Which of the following search belongs to totally ordered plan search?

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What is the advantage of totally ordered plan in constructing the plan?

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What are the possible values of the variable?

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Which variable can give the concrete form to the representation of the transition model?

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First Order Logic is also known as,

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Inference algorithm is complete only if,

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Which suggests the existence of efficient recursive algorithm for online smoothing?

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Which algorithm place two actions into a plan without specifying which should come first?

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Where does the additional variable is added in HMM?

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Which algorithm is used for solving temporal probabilistic reasoning?

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Which algorithm works by first running the standard forward pass to compute?

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Which cannot be taken as advantage for totally ordered plan search?

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Where does the additional variables are added in HMM?

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Which reveals an improvement in online smoothing?

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Which strategy is used for delaying a choice during search?

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How does the state of the process is described in HMM?

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Which algorithm is in more similar to backward chaining algorithm?

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What is the study of light?

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How many possible plans are available in partial-order solution?

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