Graph search algorithms: The graph search algorithms are used to find a particular node of a graph easily by traversing through its nodes. There are two type of graph searching algorithms are available. That are, depth-first search algorithm and breadth first search algorithm. The depth-first search has a basic level which is uniformed search where, the algorithm searches in a path until it reaches the end of the graph. After the reaching the end, the search starts at the end and backtracks to the start node and tries a different path. The breadth-first search algorithms perform searches by exploring one layer of graph at a time. Here the search starts with one level away from the start node, followed by depth level two, followed by depth level three and so on until the entire graph is traversed. Inconsistent heuristic: A heuristic function is said to be inconsistent in the analysis of path-finding problems in artificial intelligence , if its approximation is always greater than to the approximate distance from any neighbouring vertex to the target. Inconsistent heuristic can be represented as, h(N) > c(N,P) + h(P) where, h is the consistent heuristic function N is any node of the graph P is any decedent of N G is the goal node c(N,P) is the cost of reaching node P from N

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Chapter 3, Problem 24E

Program Plan Intro

Graph search algorithms:

The graph search algorithms are used to find a particular node of a graph easily by traversing through its nodes.

There are two type of graph searching algorithms are available. That are, depth-first search algorithm and breadth first search algorithm.

The depth-first search has a basic level which is uniformed search where, the algorithm searches in a path until it reaches the end of the graph. After the reaching the end, the search starts at the end and backtracks to the start node and tries a different path.

The breadth-first search algorithms perform searches by exploring one layer of graph at a time. Here the search starts with one level away from the start node, followed by depth level two, followed by depth level three and so on until the entire graph is traversed.

Inconsistent heuristic:

A heuristic function is said to be inconsistent in the analysis of path-finding problems in artificial intelligence, if its approximation is always greater than to the approximate distance from any neighbouring vertex to the target.

Inconsistent heuristic can be represented as,
h(N) > c(N,P) + h(P)

where,

h is the consistent heuristic function

N is any node of the graph

P is any decedent of N

G is the goal node

c(N,P) is the cost of reaching node P from N

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