Developed a simple reflex agent program in Python for the vacuum-cleaner world problem. This program defines the States, Goal State, Goal Test, Actions, Transition Model, and Path Cost. For each possible initial state, the program returns a sequence of actions that leads to the goal state, along with the path cost. Generates two test cases.
- Enter LOCATION A/B in captial letters where A and B are the two adjacent rooms respectively.
- Enter Status O/1 accordingly where 0 means CLEAN and 1 means DIRTY.
- Vacuum Cleaner senses the status of the other room before performing any action, also known as Environment sensing.