![]() Otherwise, make initial state as current state. If it is a goal state then stop and return success. It examines the neighboring nodes one by one and selects the first neighboring node which optimizes the current cost as the next node. Uses the Greedy approach : At any point in state space, the search moves in that direction only which optimizes the cost of function with the hope of finding the optimal solution at the end. Then this feedback is utilized by the generator in deciding the next move in the search space.Ģ. Hence we call Hill climbing a variant of generating and test algorithm as it takes the feedback from the test procedure. If the solution has been found quit else go to step 1. Test to see if this is the expected solution.ģ. The generate and test algorithm is as follows :Ģ. Variant of generate and test algorithm: It is a variant of generating and test algorithm. It helps the algorithm to select the best route out of possible routes.ġ. A heuristic function is a function that will rank all the possible alternatives at any branching step in the search algorithm based on the available information.However, it will give a good solution in a reasonable time. ‘Heuristic search’ means that this search algorithm may not find the optimal solution to the problem. ![]() Example- Travelling salesman problem where we need to minimize the distance traveled by the salesman. ![]()
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