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### 15 Cards in this Set

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 uniformed we have no problem specific reason to prefer one part of the search space to any other toward finding a part to the goal heuristic we have problem specific information to help focus the search breadth first search generates an explicit state search graph by applying all possible operators to the start node, then applying all possible operators to the direct successors of the start node, then to their successors successor function when applied to a node, it produces the entire set of nodes that can be produced by applying all of the operators that can be applied to that node uniform cost search nodes are expanded outward from the start node along contours of equal cost rather than along contours of equal depth. If the costs of all arcs in the graph are identical then uniform cost search is the same as breadth first search depth first search generates the successors of a node just one at a time by applying individual operators. A trace is left at each node to indicate that additional operators can eventually be applied there if needed. At each node, a decision must be made about which operator to apply first, which next, and so on depth bound a bound which is set which does not allow any successor to be created whose depth is greater than the depth bound chronological backtracking going back to a previous node and expanding a new path from it algorithm A* finds an optimal path to a goal(breadth first search) algorithm AO* for searching "and", "or" graphs assignment problems involves assigning values to variables subject to constraints constructive method a method where the solution is constructed step by step. Ex: place one queen first column, then place the second queen in a place that will satisfy in second column,and so on repair approach starts with a proposed solution, which most likely doesn't satisfy the constraints and repairs it until it does hill climbing a function over data structures where we seek to find a structure having a max or min value of that function. Traverse by moving from one point to that "adjacent" point having the highest elevation backed up value assume were max to choose among the tips nodes of a search tree, he would prefer the node having the largest evaluation. The backed up value of a max node parent of min tip nodes is equal to the maximum of the static evaluation of the tip nodes