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Computational Intelligence, Final Project: Quarto Agents

Contributors sID
Alessio Carachino s296138
Giuseppe Atanasio s300733
Francesco Sorrentino s301665
Francesco Di Gangi s301793

Note

ALL MEMBERS EQUALLY CONTRIBUTED TO THE PROJECT. FIRST EACH MEMBER MAINLY FOCUSED ON ONE IDEA AND THEN WE MERGED THE FINDINGS

Directory Tree

.
├── README.md
├── poetry.lock
├── pyproject.toml
└── quarto
    ├── GA_MinMaxPlayer.py
    ├── GA_Player.py
    ├── MinMax_Player.py
    ├── RandomPlayer.py
    ├── __init__.py
    ├── __pycache__
    │   ├── GA_MinMaxPlayer.cpython-310.pyc
    │   ├── GA_Player.cpython-310.pyc
    │   ├── MinMax_Player.cpython-310.pyc
    │   ├── RandomPlayer.cpython-310.pyc
    │   └── minimax.cpython-310.pyc
    ├── image.jpg
    ├── image2.jpg
    ├── main.py
    ├── main_RL.py
    ├── minimax.py
    ├── quarto
    │   ├── __init__.py
    │   ├── __pycache__
    │   │   ├── __init__.cpython-310.pyc
    │   │   └── objects.cpython-310.pyc
    │   └── objects.py
    ├── readme.md
    └── reinforcement
        ├── Memory.py
        ├── Q_data_RL_GA.dat
        ├── __init__.py
        ├── images
        │   ├── RL&GA_vs_GA_2nd_test.svg
        │   ├── RL&GA_vs_GA_2nd_train.svg
        │   ├── RL&GA_vs_GA_eps0.95_alpha0.1_train.svg
        │   ├── RL&GA_vs_GA_eps0.995_alpha0.1_train.svg
        │   ├── RL&GA_vs_GA_eps0.995_alpha0.3_train.svg
        │   ├── RL&GA_vs_GA_eps0.9995_alpha0.1_train.svg
        │   └── RL&GA_vs_Random_2nd_test.svg
        ├── rl_agent.py
        ├── tables.py
        └── utils.py

Setting up the environment

First of all you have to install poetry on your pc. Then, you have to move inside the "quarto_ci_2022_2023" folder and launch this command:

poetry install

After that, to test our code you have to launch the following:

poetry run python quarto/[main_RL or main].py

Summary

GA Agent

GA Agent is described in the GA_Player.py file. The file describes the agent using only the Genetic Algorithm strategy.

MinMax

The main file for the minmax are: minmax.py and MinMax_Player.py. These files describe the two strategies using only MinMax.

GA+MinMax Agent

GA+MinMax Agent is described in the file GA_MinMaxPlayer.py. This file describes the strategy used by our final agent: Genetic ALgorithm and MinMax.

RL Agent

RL agent is developed between rl_agent.py and main_RL.py.

Conclusion

The best strategy is to use the GA_MinMaxPlayer.py, that is the combination of MinMax and Genetic Algorithm.