Greedy Best First Search-Artificial Intelligence-Unit – 1 -Problem Solving -Informed Searching

Unit – 1 – Problem Solving Informed Searching Strategies - Greedy Best First Search Greedy best-first search algorithm always selects the path which appears best at that moment. It is the combination of depth-first search and breadth-first search algorithms. It uses the heuristic function and search. With the help of best-first search, at each step, we can choose the most promising node. In the best first search algorithm, we expand the node which is closest to the goal node and the minimum cost is estimated by heuristic function The evaluation function is f(n) = h(n) Were, h(n)= estimated cost from node n to the goal. Greedy search ignores the cost of the path that has already been traversed to reach n Therefore, the solution given is not necessarily optimal Greedy best-first search can start down an infinite path and never return to try other possibilities, it is incomplete Because of its greediness the search makes choices that can lead to a dead end; then one backs up in the search tree to the deepest unexpanded node Greedy best-first search resembles depth-first search in the way it prefers to follow a single path all the way to the goal, but will back up when it hits a dead end The quality of the heuristic function determines the practical usability of greedy search Greedy search is not optimal Greedy search is incomplete without systematic checking of repeated states. In the worst case, the Time and Space Complexity of Greedy Search are both O( b m ), Where b is the branching factor and m the maximum path length Subscribe this channel, comment and share with your friends. For Syllabus, Text Books, Materials and Previous University Question Papers and important questions Follow me on Blog : https://dsumathi.blogspot.com/ Facebook Page : https://www.facebook.com/profile.php?id=100064221514856 Instagram : https://www.instagram.com/dsumathiphd/