Evaluating Search Strategies

We have many searching techniques  that we have discussed as uninformed but to evaluate such search strategies we talk  about the following four Completeness Completeness is a guarantee of  finding a solution whenever  one  exists.This means that if a solution exists andif you are searching technique can find that solutionRead More →

Cost Of Solution

1.Cost of  solution is the sum of the arc costs on the solution path. • If all arcs have the same (unit) cost, then the solution cost is just the length of solution (number of steps/state transitions).then the solution cost is just the length of the solution or the numberRead More →

The notion of a path in a graph is  clear and is shown below •             Suppose G (V,E) is a graph with vertices v¬0, v1,v2,……,vk. and edges are e1,e2,……..,ek in which edge  ei={vi-1,vi} for i= 1,…,k. •             The alternating sequence that I get of vertices and edges , starting fromRead More →

Uninformed search does not have any domain knowledge. Here we are going to learn about some uniformed search strategies. Before getting into this take a review on problem solving as search, state spaces, graph searching and generic searching algorithms. We have previously learnt about the general definitions of problem solvingRead More →

Nodes labeled by component databases have sets of successor nodes each labeled by one of the components. These nodes are called AND nodes because in order to process the compound database to termination all of the component database must be processed to termination.  In the above figure 2,  this nodeRead More →

A graph search control strategy might explore many equivalent paths in producing a database containing only M’s. Redundant Paths can lead to inefficiencies because the control strategy might attempt to explore all of them; worse it might do work that is wasted ultimately in exploring paths that do not terminate.Read More →