I. Lowest-cost-first search Today we explored another form of blind search called lowest-cost-first search. Lowest-cost-first search is an attempt to use information about the problem at hand (once again the 8-tile puzzle in our example) to guide the search. The information in this case is the cost of the paths from the start node to the nodes on the frontier. Recall that depth-first-search chooses the node most recently added to the frontier list as the next node to be explored, while breadth-first-search chooses the least recently added (i.e., the oldest) node on the frontier. Lowest-cost-first search is different from these only in that it chooses the node from the frontier with the lowest cost path from the start node to that node. If the individual arc costs are the same, then lowest-cost-first search becomes breadth-first-search. II. Comparing blind search strategies After that scintillating discussion of lowest-cost- first search, we did a little comparison of the behaviors of these three variations on the blind search theme. Here are some of the points that were raised. Your textbook brings up more points, and you should read those. All will find a solution in a finite space if a solution exists Depth-first can get trapped in infinite recursion in an infinite space (except in CILOG) Breadth-first and lowest-cost will find a solution even in an infinite space, if one exists Breadth-first will find path to goal with fewest arcs Lowest-cost-first will find lowest cost path (of course) when arcs have different costs Breadth-first is just depth-first but adding to frontier differently Lowest-cost-first is just breadth-first with more information and sorting Breadth-first and lowest-cost-first seem wonderful, but they're gigantic space hogs in terms of how big frontier can be There's a whole lot more of this good vs. bad stuff in your textbook (chapter 4.4)...read it Ultimately, all three are expensive approaches to search And that last point leads us to the question of how to make search less computationally expensive. That's the topic of the next lecture.
Last revised: October 28, 2004