Based on the book Artificial Intelligence: A Modern Approach, and python repository provided.
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main.py - main file to be run from command prompt
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QueensEnv(ironment):
- Table - wrapper class to hold agent, it's board and performance measure
- Statistics Module - gathers all statistical information about current run
- Agents - contains definitions of generator objects. Those are function-like creatures which remember their internal state and return a new value every time .send() is called. Initialisation is done with .send(None), in this case used to print agent's name. This structure is meant to represent functional nature of agent, as proposed in the book/original repo. May be changed as desired.
- Utility Measures - implementation of utility function used by all agents so far, i.e. the number of pairs which check each other.
A board with 8 queens on it is encoded by their y coordinates, assuming there is exactly one queen in each column. Simple plot utility plot_board() is provided in StatsModule.py. For example, board encoded as [0,1,2,3,4,5,7,7] will render to:
![sample_board.png][./sample_board.png]
This code requires Python 3.4 or later, and does not run in Python 2. You can install Python or use a browser-based Python interpreter such as repl.it.
You can run the code in an IDE, or from the command line with python -i filename.py where the -i option puts you in an interactive loop where you can run Python functions. See jupyter.org for instructions on setting up your own Jupyter notebook environment, or run the notebooks online with try.jupiter.org.