In what ways are DFS and Best-first search similar? How are BFS and Best-first similar?
To me, to better decribe how DFS and BestFS are similar, it might be easier to point the difference,which is that in BestFS we chose as the next to expand the one that seems closest to the goal using the heuristi function. In almost all other ways both of the best and DFS are similar.
However I find it hard to find the similarities between BFS and BestFS
Hi
Best First Search is a type of informed search and suits well in scenarios where some information about the state space you are searching is known. This acquaintance with the state space or the system you are working in, helps in developing a heuristic which decides the best node at each search step. In a nutshell, Best First Search uses Greedy paradigm to approach a goal i.e. your search target.
Depth First Search and Breadth First Search are uninformed search methods and are handy when you know nothing about the system you are dealing with. They have their own trade-offs (among themselves) in terms of memory and guarantee to find a solution (if it exists). You can check the details in Wiki.
I don't see much of a similarity between the uninformed search and informed search methods except that they help solve the search problem. Another aspect on which the similarity can be argued is whether a search is complete (search method is called complete when it returns a solution whenever one exists) and optimal (search method is optimal when it returns a minimum cost path solution whenever a solution exists).
Breadth First Search - Complete and Optimal (if all edges have unit cost)
Depth First Search - Complete (for finite search tree) and not optimal
Best First Search - Complete and Optimal
The key is to know which one to use in what situation.
I hope this helps.
cheers