Milad Pourrahmani is a physics PhD candidate at the University of California, Irvine. He specializes in observational cosmology and has developed a deep learning algorithm that can identify strong gravitational lenses among millions of galaxy images. Not only he is interested in their applications, but he also wishes to study and develop artificial neural networks in their own right after completing his degree. Milad is a strong proponent of computational thinking, enjoys developing fun computational experiments in Mathematica and likes playing music.
Project: A New Kind of Chess
The rules of chess have been perfected for more than a millennia to ensure an exciting game every time. These relatively simple rules are capable of producing very interesting and complex dynamics that deserve to be studied in their own right, not just merely for competition purposes. This project aims at laying down the formalism to capture the game of chess as well as many other board and card games. In accordance with this formalism, a Mathematica chess package has been developed that creates, displays and evolves a ChessState object using the ChessState, ChessPlot and ChessEvolve functions.
Main Results in Detail
ChessPlot enables the user to provide options such as board color set, display coordinates, rotate point of view or extract MatrixForm of a ChessState. In addition, a list of rule functions is provided that takes in a ChessState and outputs all of the possible moves in accordance with the rule they represent.
With this setup, the user is able to set up any ChessEvaluate function and explore the chess space. This open-ended chess design also enables the user to modify the rules with ease so they can explore chess variations such as antichess, atomic chess and others.