Assignment 1
                  Introduction to Agents
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           All work is to be done independently.
       Consult only your TAs or the instructor should you
                   have questions.
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                   Due Tuesday 1/23 in class.

               Late asssignments will not be accepted.
               Turn in whatever you have at that time for
               partial credit.  Do not ask for an extension.
                       *** Plan ahead ***
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1. Answer questions 1.2, 1.3, 1.8, and 2.3 from the text. Make sure that you
   explain the reasoning behind your answers.

2. To answer the following questions, you 'll need to do the following:
   From acme or a CoC Sun:
   A. Invoke lisp (either with lisp or cl command, depending on the system)
   B. Then type:
         for acme
             (load "~arkin/aima/aima.lisp")
       or for CoC Sun
             (load "/net/faculty/ai/arkin/aima/aima.lisp")
      Ignore warnings regarding packages
   C. Then type:
             (aima-load 'agents)
    D. Then type (test) to see an example run to get a feel for how the
       system works.

   The source code for these systems is in:
       acme: ~arkin/aima/agents and ~arkin/aima/utilities  
       sun: /net/faculty/ai/arkin/aima/agents and .../utilities
   ===========
  Answer the following questions from the text:
    2.7 create variable environments 
    2.9 Create at least the following two state-based agents
         a) One which remembers its last move (previous location)
         b) One which remembers its last three positions
             The agents should use this state info to avoid revisiting
               sites already known to be vacuumed.
    2.11 Use variable environments with multiple agents (use the provided
         random-agent and reactive-vacuum-agent plus the state agents from 2.9)
         comparing performance measures. Make sure you analyze their
           performance and discuss what you find.

      Turn in all code that you generate/modify (hardcopy), and test results
       demonstrating your successful runs.

Extra Credit: Create an agent capable of remembering the entire spatial
    layout that it has traveled for a world that may be as large as 20 by 20
    units. Devise an efficient means by which this information can be used by 
    the agent to move around in various vacuum worlds.
    Compare its performance to the other agents above.
     -- A competition will be held to determine the best agents --