This AI agent is specifically designed to play the game of Clobber, a strategic board game in which players take turns placing their pieces on a grid and trying to capture their opponent's pieces by surrounding them.
To find the most optimal moves in Clobber, the Agent uses a search algorithm called Principal Variation Search, also known as Negated Scout. This algorithm works by evaluating different possible move combinations and selecting the one that leads to the best outcome for the player.
In addition to Principal Variation Search, the Clobber-AI-Agent also employs other techniques to improve the accuracy of its search. For example, it uses move ordering to prioritize certain moves over others.
This notebook was originally submitted as an assignment for a course in my bachelor's degree, and has since been refined and updated.If you have any questions or suggestions for improvement, don't hesitate to reach out!