What is the main idea of Informed Search?, Search without any additional information, Use domain-specific knowledge to guide the search, Always expand the deepest node, Always expand the shallowest node, What does the heuristic function h(n) estimate?, The actual cost from the initial state to n, The total number of nodes in the tree, The estimated cost from n to the goal, The depth of node n, ?What does g(n) represent, Estimated cost from n to the goal, Total number of successors of n, Path cost from the initial node to n, Heuristic value of n, ?What does f(n) represent in Best-First Search, An evaluation function used to select a node for expansion, The depth of the node, The number of children of the node, The goal test, ?In Best-First Search, which node is generally expanded first, The node with the highest cost, The node with the lowest evaluation value, The deepest node, The oldest node, ?Greedy Best-First Search uses which evaluation function, f(n) = g(n), f(n) = g(n) + h(n), f(n) = h(n), f(n) = g(n) − h(n), ?Why is Greedy Best-First Search called “greedy”, It always chooses the cheapest complete path, It tries to get as close to the goal as possible at each step, It explores every possible path, It always chooses the deepest node, Is Greedy Best-First Search guaranteed to find the optimal solution?, Yes, always, Yes, if the branching factor is finite, No, Only when h(n) = 0, What heuristic is used in the Romania route-planning example?, Manhattan distance, Straight-line distance, Euclidean path cost, Number of cities visited

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