artificial intelligence problem spaces and search

artificial intelligence problem spaces and search

Problems, Problem Spaces, and Search:

In the last chapter, we gave a brief description of the kinds of problems with which Al is Typically concerned, as well as a couple of examples of the techniques it offers to solve those problems. To build a system to solve a particular problem, we need to do four things:

1. Define the problem precisely. This definition must include precise specifications

of what the initial situation(s) will be as well as what final situations constitute acceptable solutions to the problem.

2/Analyze the problem. A few very important features can have an immense impact

on the appropriateness of various possible techniques for solving the problem.

3. Isolate and represent the task knowledge that is necessary to solve the problem.

4. Choose the best problem-solving technique(s) and apply it (them) to the particular V problem.

In this chapter and the next, we discuss the first two and the last of these is Then, in the chapters in Part II, we focus on the issue of knowledge representation

2.V Defining The problem as a State Space Search

Suppose we start with the problem statement "Play chess." Although there are a lot of people to whom we could say that and reasonably expect that they will do as we intended, as our request now stands it is a very incomplete statement of the problem we want solving.

 To build a program that could "Play chess," we would first have to specify the starting position of the chessboard, the rules that define the legal moves, and the board positions that represent a win for one side or the other. In addition, we must make explicit the previously implicit goal of not only playing a legal game of chess but also winning the game, if possible.