Problem Solving using Search

1. Problem Solving using Search

The focus of much AI research has been on solving problems. Much of the point of the AI research was to understand “how” to solve the problem, not just to get a solution. So seemingly simple problems—puzzles, games, stacking blocks—were the focus of AI programs. And one of the first areas of work, general problem-solving methods, highlighted a major barrier to artificial intelligence software. How do you represent a problem so that the computer can solve it? Even before that, how do you define the problem with enough precision so that you can figure out how to represent it?

Steps of solving the problem are:-
a- Clearly and succinctly define what it is we are trying to do.
b- Clarifying of how to represent our problem “representation” so that we can solve it using search techniques.
c- Which search techniques are best to solve the problem?

We explore one of the primary problem representations, the state-space approach.
Example : Suppose that the problem we want to solve deals with playing and winning a game. This game could be a simple one such as tic-tac-toe or a more complex one such as checkers, chess, or backgammon
To solve each problem in AI, we need these Steps:-
? initial state, which ¬in the case of tic-tac-toe could be a 3 by 3 matrix filled with spaces (or empty markers).
? Operators (Control Strategy) : This can be used to modify the current state, thereby creating a new state. In our case, this would be a player marking an empty space with either an X or an O.