What is the difference between uniform-cost search and best-first search methods?

Question

I observed that both these methods have data structure which holds the nodes to expand. Both methods first expand the node with the best cost. So,what is the difference between them?

I read that uniform-cost search is a blind method and best-first search isn't which is even more confusing.

Answer 1

It is true that both the methods have a list of expanded nodes but Best-first search tries to minimize the expanded nodes using both the path cost and heuristic function.

The difference between Uniform-cost search and Best-first search are as follows-

1. Uniform-cost search is uninformed search whereas Best-first search is informed search.
2. Uniform cost search expands the least cost node but Best-first search expands the least node.
3. Uniform cost search cannot deal with heuristic function ,so f(n)=g(n) where g(n) is the path cost . Ex- number of moves ,etc.                                                                                   Best-first search does deal with heuristic function,so f (n) = g(n) + h(n) where g(n) is the path cost and h(n) is the heuristic function.Ex- A* algorithm.

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Answer 2

It is true that both the methods have a list of expanded nodes but the Best-first search tries to minimize the expanded nodes using both the path cost and heuristic function.

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