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AI Algorithms (MESIIN476025)

AI Algorithms (MESIIN476025)

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In the following plot, identify a starting point which would lead to a suboptimal solution (local maximum), if we used Hill Climbing.

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Consider the state space graph below. Goal states are those colored in green. Nodes are expanded from left to right when there are ties. What solution path is returned by DFS?

I-A-D-F-H

100%

I-C-E-G

I-A-G

I-A-D-F-J

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In the following plot, identify a starting point which would lead to a suboptimal solution (local maximum), if we used Hill Climbing.

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In Simulated Annealing, if the current state's evaluation function value is a positive value , and the selected neighbor state's value is greater than or equal to , how does the probability of moving to this neighbor change as the temperature is gradually decreased? Assume we are maximizing the evaluation function.

It doesn't change, it's always 0

It increases

It decreases

It doesn't change, it's always 1

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In the context of local search algorithms, what is a 'neighborhood'?

A subset of solutions derived from small changes to a current solution.

100%

The initial state from which the search begins.

The set of all possible solutions to a problem.

The final solution obtained after the search process.

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In the following plot, identify a starting point which would lead to a suboptimal solution (local maximum), if we used Hill Climbing.

100%

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Uniform-cost search will never expand more nodes than A*-search.

True

False

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Consider the state space graph below. Goal states are those colored in green. Nodes are expanded from left to right when there are ties. What solution path is returned by DFS?