7. A profile hidden Markov model (profile HMM) as shown below is used to model a multiple alignment. Delete Delete Delete Insert Insert Insert Insert Begin Match Match Match Match Match End Explain the roles of the following states in the profile HMM. i) Match ii) Insert iii) Delete
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- Consider a knowledge base (KB) shown in Figure4. Assume that the initial fact base from a user is {Q /\ N} and the goal state {S}. Based on the initial facts and goal state, show the backward chaining and forward chaining searchpathsFor historical data sets, it is important to describe the hidden Markov chain.Do the following.i. Generate a four state Markov Chain matrix of your own choice make sure eachrow sum up to one.ii. Draw the state diagram of Markov chain.iii. Create another matrix with 4 states and draw its state diagram. Make sure eachrows sum up to 1.iv. Multiply both matrix and make sure the first matrix should be on the left and thesecond right. Ensure that each row sum up to one.v. Draw the state diagram final state.
- Consider the following knowledge base Prove that Q is true with: 1. P → Q 2. L ∧ M → P 3. B ∧ L → M 4. A ∧ P → L 5. A ∧ B → L 6. A 7. B Forward-Chaining Backward-Chaining Resolution Prove t → s: 1. p → q 2. [q ∧ r] → s 3. [t ∧ u] → r 4. u → w 5. t → y 6. y → u 7. r → p 8. p → m i. Express in clause form ii. Forward-Chaining iii. Backward-Chaining iv. ResolutionThe importance of the hidden Markov chain in a historical data set should be discussed.How many states have a nonsimplified Markov chain for a system consistingof n components? Assume that each component has two states: operationaland failed.
- You are required to create a Julia program that does the following in this problem:Analyze every policy you are given, then tweak it until a solution is discovered. Real-time recording and saving of the Markov decision process (MDP).Consider the following knowledge base in first order logic: p(X) ← q(X) ∧ r(X, Y ) q(X) ← s(X) ∧ r(Y, Y ) s(a) r(a, a) What is the result of the query p(a) using a backward chaining inference algorithm? Show the intermediary queries.If the problem can be addressed by devising optimal subproblem solutions, it has the attribute. Memory, greedy subproblems, overlapping subproblems
- can you please help me understand how resource allocation graph algorithm becomes a deadlock avoidance? no handwritten answers please, no one worded, one phrased, or one sentenced answers too pleaseConstruct an optimal binary search tree for five keys A, B, C, D, E with probabilities p1 = 0.1, p2 = 0.3, p3 = 0.1, p4 = 0.4, p5 = 0.1. Show(1) the main table; (2) the root table; (3) all computations to fill in the main table and the root table; (4) the optimal binary search tree based on the root table; (5) that the average number of comparisons of your optimal binary search tree is indeed C(1,5).Question 15 pap In class we considered the computational complexity of global localization as a hypothesis elimination problem in an idealized setting. What is this problem (briefly), how difficult is it to get an optimal solution (i.e. do you know the complexity?), and what kind of heuristic can be used to achieve a solution?