The Least-Cost search is the exact opposite of the hill-climbing search. An analogy can also be used to demonstrate this search. Remember our hiker from the hill-climbing example? Well, he found his way back to the camp at the top of the mountain and it started to snow. So, he walks back down to the McDonalds half way down the mountain for a breakfast burrito. When he gets there, the mountain is covered with snow, so he gets himself some coffee and then set back up the mountain. Now at this point he finds a sled and gets on. He finds that it is much easier to go down than go up. But, anyway, this is just a more interesting way of saying that the Least-Cost method takes the path of least resistance. The search finds the easiest way to the solution regardless of how many nodes the path encounters.

Advantages:
• Reduces cost of nodes visited
Disadvantages:
• “False valleys” in which extensive backtracking occurs
• All nodes may look equally good