[Solved]: Difference between heuristic-based searching and optimal path searching

Problem Detail: 

I'm currently studying for an AI computer-science course. One thing is difficult for me to grasp and somewhat vaguely explained in my course-material:

I understand that with search-methods like e.g. beam search, hill-climbing... you can search based on a certain knowledge about the problem which can tell you in each state an approximation off how close you are to finding the solution. Currently I've reached a chapter about Optimal Search algorithms. An important algorithm in that chapter is Uniform Cost which is based on the lowest accumulated "travel-cost", with as desired consequence that the algorithm will reach a solution in a branch with the lowest accumulated travel cost. Now, I don't understand that travel cost and how it differs from a normal heuristic value. Can someone explain the difference and how it effects finding a solution?

Asked By : CedricCornelis

Answered By : D.W.

Uniform Cost Search (UCS) does not have a heuristic value and doesn't rely on a heuristic function. I suspect you're getting it confused with some other algorithm (e.g., A*). In Uniform Cost Search, there's no heuristic: we know exactly what the distance from the starting point was, and we use that to determine which nodes to expand.

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Question Source : http://cs.stackexchange.com/questions/51911

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