A driver for the wumpus world which allows for students to create their own Wumpus World agent to navigate the cave.

The simulator works by generating a new world and a new agent for each trial. Before each try on this world, the agent's Initialize() method is called, which you can use to perform any pre-game preparation. Then, the game starts. The agent's Process() method is called with the current Percept, and the agent should return an action, which is performed in the simulator. This continues until the game is over (agent dies or leaves cave) or the maximum number of moves (1000) is exceeded. When the game is over, the Agent's GameOver() method is called. If additional tries are left for this world, then the world is re-initialized, and the agent's Initialize() method is called again, and play proceeds on another instance of the same game.

After the number of tries is completed, the agent is deleted. So, you may want to store some information in the agent's destructor method to be reloaded during the agent's constructor method when reborn for the next trial. If additional trials have been requested, then a new wumpus world is generated, and the process continues as described above.

Scoring information is output at the end of each try, each trial and at the end of the simulation.

Your agent must include at least five methods: constructor, destructor, Initialize, Process, and GameOver. You may change any or all of these methods to implement your agent. And you may include additional methods as you see fit.

You will make all your changes to the PyAgent.py file. You will see five functions in the file: PyAgent_Constructor, PyAgent_Destructor, PyAgent_Initialize, PyAgent_Process, and PyAgent_GameOver. These five functions are called by their counterparts in the simulator. You can see how this is done in the Wumpsim.py file, BUT DO NOT MODIFY THIS FILE. The only file you should change is PyAgent.py. Note that the PyAgent_Process function takes the five separate percepts, rather than a Percept class instance, and the PyAgent_Process function should return one of the six actions defined in the Action.py file.

Once you've finished your PyAgent.py file, simply run the python Wumpsim.py program to test your agent. The PyAgent.py file and the Wumpsim.py script must be in the same directory. The Wumpsim.py program accepts all the simulator options described described below.

The following options are allowed and provided to the simulator as arguments:

usage: MyWumpsim.py [-h] [-tries TRIES] [-trials TRIALS] [-seed SEED]

Optional Arguments:
  -trials TRIALS
    The number of trials to attempt. Each trial will generate a new world
    to test the agent on. Default is 1.
  
  -tries TRIES
    The number of tries attempted for each trial which will give the agent
    multiple tries for eahc world that is created. Default is 1.
  
  -seed SEED
    The seed to specify to the random number generator. Specifying a seed 
    allows for the simulator to run the same random worlds.
    Default is None which uses a random component from the system time.
    
  -world WORLD
    The world file to as a pre-defined wumpus world. The file must follow a
    specified format (example is 'testworld.txt'):
      size N      # the size of the world (integer)
      wumpus X Y  # the (x,y) location of the wumpus (integers)
      gold X Y    # the (x,y) location of the gold (integers)
      pit X Y     # the (x,y) location of a pit (integers)
                  # subsequent lines may include additional pit locations

This project was based on the wumpus simulator by Larry Holder:

Wumpus Simulator v2.9 (released 09/15/2017)
Copyright (c) 2017. Washington State University.
Written by Larry Holder ([email protected]).

The Python version of this simulator project was written for the CPE 480 class in Artificial Intelligence at Cal Poly, San Luis Obispo, CA to replace the C++ implementation.

Currently this version of the simulator does not support importing a predefined world from a text file like the original verson of the wumpus simulator. All the worlds will have to be randomly generated.

• Version 1.0 only supports Python 2.7
• Version 1.1 now supports Python 3 (print statements were updated in the driver)
• Version 1.2 now supports loading pre-defined worlds