Problem Solving Agent

As your search agent becomes more sophisticated, you may give it more information to produce better routes.

As your search agent becomes more sophisticated, you may give it more information to produce better routes.

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Suppose the problem we had set our agent was to find a name for a newborn baby, with some properties.

In this case, there are lists of "accepted" names for babies, and any solution must appear in that list, so goal-checking amounts to simply testing whether the name appears in the list.

Before we worry about exactly what strategy to use, the following need to be taken into consideration: Broadly speaking, there are two different reasons to undertake a search: to find an artefact (a particular state), or to find a path from one given state to another given state.

Whether you are searching for a path or an artefact will affect many aspects of your agent's search, including its goal test, what it records along the way and the search strategies available to you.

If you can think of the task you want your agent to perform in these terms, then you will need to write a problem solving agent which uses search.

It is important to identify the scope of your task in terms of the problems which will need to be solved.

For example, in the maze below, the game involves finding a route from the top left hand corner to the bottom right hand corner.

We all know what the exit looks like (a gap in the outer wall), so we do not search for an artefact.

For instance, there are some tasks which are single problems solved by searching, e.g., find a route on a map.

Alternatively, there are tasks such as winning at chess, which have to be broken down into sub-problems (searching for the best move at each stage).