Full text of the second edition of Artificial Intelligence: foundations of computational agents, Cambridge University Press, 2017 is now available.

## 3.3 Graph Searching

In this chapter, we abstract the general mechanism of searching and present it in terms of searching for paths in directed graphs. To solve a problem, first define the underlying search space and then apply a search algorithm to that search space. Many problem-solving tasks can be transformed into the problem of finding a path in a graph. Searching in graphs provides an appropriate level of abstraction within which to study simple problem solving independent of a particular domain.

A (directed) graph consists of a set of nodes and a set of directed arcs between nodes. The idea is to find a path along these arcs from a start node to a goal node.

The abstraction is necessary because there may be more than one way to represent a problem as a graph. Whereas the examples in this chapter are in terms of state-space searching, where nodes represent states and arcs represent actions, future chapters consider different ways to represent problems as graphs to search.