Assignment 1: Environments and reflex agents

This assignment tests the understanding of simple reflex agents and the ways in which they interact with their environments.

1. (exercise 2.7 from AIMA) Implement a performance measuring environment environment simulator for the vacuum-cleaner world depicted below:

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It should have the following characteristics:

• The performance measure awards one point for each clean square at each time step over a lifetime of 1000 steps.
• The "geography" of the environment is known a priori but the dirt distribution and initial location of the agent are not. Clean squares always stay clean and sucking cleans the current square. The Left and Right actions move the agent left and right except when this would take the agent outside the environment, in which case the agent remains where it is.
• The only available actions are Left, Right, Suck and NoOp (do nothing).
• The agent correctly perceives its location and whether that location contains dirt.

Your implementation should be modular, so that the sensors, actuators and environment characteristics (size, shape, dirt placement etc.) can be changed easily.

2. (Exercise 2.8 from AIMA) Implement a simple refex agent for this environment. Run the environment simulator with this agent for all possible dirt configurations and agent locations. Record the agent's performance score for each configuration and its overall average score.

Language

You may use any progrmaming language available in the CS domain (ask me if you want to use Scheme).

Due Date

Submit your file(s) through the file submitter by midnight on February 6th.