Desktop Reversi game made in Kotlin and Swing. The project focuses on implementing and exploring AI algorithms for zero-sum games, including MinMax, Alpha-Beta pruning, and various heuristics.
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Updated
Jun 9, 2017 - Kotlin
Desktop Reversi game made in Kotlin and Swing. The project focuses on implementing and exploring AI algorithms for zero-sum games, including MinMax, Alpha-Beta pruning, and various heuristics.
Some applications of optimization using linear, binary, and integer programming.
A tic tac toe game with an AI that you just can't beat
Demonstration of the concept of convergence for the Fictitious Play algorithm, simulating a simple zero-sum game over multiple iterations.
Psychopy implementation of the article : "Neural computations underpinning the strategic management of influence in advice giving" by Uri Hertz & BB
A minimax algorithm to solve a two-player connection board game
Simulating the game theory behind Linaia-Agon by Iannis Xenakis
my favorite projects
A 2D JavaFX implementation of one of the most popular and old board games. The AI player's moves are calculated using the expectiminimax algorithm.
A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.
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