heuristic search fig breadth first search of maze while it would be nice to be able to find optimal solutions to problemsbreadth first search is not really all that practical to use most interesting problems have high enough branching factors that breadth first search is impractical hill climbing depth first search was impractical because it blindly searched for solution if the search is truly blind then sometimes we'll get lucky and find solution quickly while other times we might not find solution at all depending on the size of the search spaceespecially when there are infinite branches if we had some more information about where the goal isthen we might be able to improve the depth first search algorithm think of trying to summit mountain we can see the peak of the mountain so we know the general direction we want to take to get there we want to climb the hill that' where the name of this algorithm comes from anyone who has climbed mountains knows that sometimes what appears to be route up the mountain leads to dead end sometimes what appears to be route to the top only leads to smaller peak close by these false peaks are called localized maxima and hill climbing can suffer from finding localized maximum and thinking that it is the overall goal that was sought hill climbing example figure features the same maze with hill climbing applied to the search to climb the hill we apply heuristic to help in searching mazeif we know the exit point of this copy belongs to 'acha