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A semester-long project about AI vs. Human version of the Italian card game Briscola using Machine Learning, Reinforcement Learning, Adversarial Search, Markov Decision Process, Minimax algorithm and Monte Carlo Tree Search.

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Briscola-Project

A semester-long group project split into 3 phases. Please consult 2021-2022-2-1_ProjectManual-PlayIt_final.pdf for more information about the project and its phases.

Our code for each phase is in a separate folder and inside there's a README file that explains how to run the code.

Short summary: We first implemented Human vs. Human version of the Italian card game Briscola in Java with GUI using JavaFX. Then, we created Human vs. AI version using Machine Learning, Reinforcement Learning, Adversarial Search, Markov Decision Process, Minimax algorithm and Monte Carlo Tree Search.

For further explanation of what we did, please consult FinalReport.pdf.

Group members: Alisa Todorova, Oscar von Moeller, Parand Mohri, Joaquin Monedero Simon, Hemachandra Konduru, Alexander Safi

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A semester-long project about AI vs. Human version of the Italian card game Briscola using Machine Learning, Reinforcement Learning, Adversarial Search, Markov Decision Process, Minimax algorithm and Monte Carlo Tree Search.

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