Connect 4 with AI powered by Monte Carlo Tree Search.
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Updated
Jun 10, 2017 - Java
Connect 4 with AI powered by Monte Carlo Tree Search.
An ISMCTS AI for the card game Schnapsen
Unbeatable AI for the tic tac toe.
An implementation of MinMax and Monte Carlo Tree Search solvers for Connect 4.
A generalized multithreaded artificial intelligence capable of playing: Connect Four, Hex (7 x 7), Reversi (Othello), and Tic-Tac-Toe.
Gobang game and AI implemented with monte carlo tree search in javascript
Efficient algorithm for making informed decisions in games and other decision-making scenarios. It combines elements of simulation, random sampling, and decision tree analysis to make accurate predictions in real-time. The algorithm is written in Kotlin, a modern and expressive programming language, making it easy to understand and modify.
explorations of Scheme synthesis in Scheme
🌲 Teaching an AI to solve Sokoban using AlphaGo-Zero style RL & Single-Player MCTS.
GenesisZERO : potential applications for MCTS agents with LLMs for Sequential decision-making
Ultimate Tic Tac Toe for Android
This repository contains a Python implementation of the classic game Tic Tac Toe with AI opponent. The game is played on a 3x3 grid by two players, one using 'X' and the other using 'O'. The player who first gets 3 of their marks in a row (up, down, across, or diagonally) is the winner.
This web application provides a comprehensive platform for testing and interacting with various AI agents developed for the ConnectX game. Built with a React frontend and a Python Flask backend, this platform offers a visually engaging interface that allows users to easily interact with and evaluate the performance of different game AI agents.
This repository contains an implementation of checkers where different agents play against each other using different algorithms including Monte Carlo Tree Search, Alpha-Beta Pruning, and Minimax.
A programming language for implementing turn-based games with complex rule sets. (with built in Monte Carlo Tree Search AI!)
Monte Carlo Tree Search (MCTS) combined with Reinforcement Learning (RL) and Deep Learning (DL) to play the board game Hex
Various AIs for the board game hex, including Monte Carlo Tree Search with the Tsetlin Machine
General N x N x K game with a GUI and AI. Can be used to play Tic Tac Toe or Gomoku. AI uses MiniMax and UCT Monte Carlo Search Tree. Read Guide.pdf.
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