Combining cost-so-far and heuristic function
{"Image DocumentName": "Combining cost-so-far and heuristic function", "Image ImageDescription": "We can combine the strengths of uniform-cost search and greedy search. Since what we re really looking for is the optimal path between the initial state, and some goal state, a better measure of how promising a state is, is the sum of the cost-so-far, and our best estimate of the cost from there to the nearest goal state. For a state n, with a cost-so-far g(n), and a heuristic estimate of the cost to goal of h(n), what we want is: f(n) = g(n) + h(n) This proves to be a very effective strategy for controlling state-space search. When used with best-first search, as a way of sorting the agenda---where the agenda is sorted so that the states with the lowest values of f(n) come first, and are therefore expanded first---this is known as Algorithm A. 21/10/04. AIPP Lecture 9: Informed Search Strategies.", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}