Vacuum cleaner

Consider a Vacuum cleaner world

 

Imagine that our intelligent agent is a robot vacuum cleaner.
Let's suppose that the world has just two rooms. The robot can be in either room and there can be dirt in zero, one, or two rooms. 

Goal formulation: intuitively, we want all the dirt cleaned up. Formally, the goal is

 { state 7, state 8 }.

Problem formulation(Actions):Left,Right,Suck,NoOp

 State Space Graph:

Measuring performance

With any intelligent agent, we want it to find a (good) solution and not spend forever doing it.

The interesting quantities are, therefore,

• the search cost--how long the agent takes to come up with the solution to the problem, and
• the path cost--how expensive the actions in the solution are.

The total cost of the solution is the sum of the above two quantities.