The python implementation of Partition-based Random Search for stochastic multi-objective optimization via simulation
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Updated
Oct 4, 2017 - C
The python implementation of Partition-based Random Search for stochastic multi-objective optimization via simulation
A simple curses connect 4 game to be enjoyed in the terminal.
Component-oriented 2D game engine for OpenFrameworks
A high performance Ultimate Tic-Tac-Toe engine in the browser
Performant multi-threaded MCTS AI for Connect Four
AI Agent that plays Nine Board Tic Tac Toe game
IS-MCTS agent for Legends of Code and Magic (WIP)
Implementation of Monte Carlo Tree Search along with two zero-sum games as it's use case
A program I wrote for CS-1203 Data Structures. I implement Monte Carlo Tree Search in C to play Tic Tac Toe. My original plan was to do this for Ultimate Tic Tac Toe, but I found that that was needlessly complicated and that it would be better to just implement Monte Carlo Tree Search for a simpler game to demonstrate my technical knowledge.
Various AIs for the board game hex, including Monte Carlo Tree Search with the Tsetlin Machine
Tic Tac Toe playing MCTS agent, written in C99.
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