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A fast C++ impementation of Monte Carlo Tree Search with abstract classes that a user of this library can extend in order to use it. To demonstrate it I apply it to the game of Quoridor.
In this project we try to create a sophisticated computer agent to play the Contact Bridge card game. Our goal is to develop an agent that is tough to play against, with fast reaction time so it is able to play in real time against humans. We approached this as a search problem, and implemented search-tree heuristics based on Minimax and Monte Carlo Tree Search. Implemented as a final project for the "Introduction to Aritifical Intelligence" course of the Hebrew University of Jerusalem.
Recombining and concurrent Monte Carlo tree search
A solver for the game of Tak as described in Patrick Rothfuss's Kingkiller Chronicles.
AI for the Connect 4 game
Implementation of an AlphaGo Zero paper in one C++ header file without any dependencies
A connect-4 gaming AI based on Monte Carlo Tree Search
The content of this repository will be inherent to the Computational Intelligence course at Polytechnic University of Turin academic year 2023/2024
Strong Aritifical Intelligence for Checkers created using Upper Confidence Tree algorithm with GUI.
An AI of hexagon gobang, using mcts
AI implementation using monte carlo tree search (MCTS) for the Game of Amazons
Sentiment Analysis & Monte Carlo Tree Search with Nested Rollout Policy Adaptation for Business
An implementation of Monte Carlo Tree Search for Domineering written for a competition organized by Johannes stöhr.
Monte Carlo Tree Search algorithm applied to a simplified version of Blizzard's Hearthstone. Explores various types of greedy AI agents to learn from and beat down. A part of Reinforcement Learning class at Wrocław University of Science and Technology
Tic-tac-toe/"noughts & crosses" written in Clojure (CLI + deps). AI powered by Monte Carlo tree search algorithm
Simple implementation of MCTS in checkers
An RL bot based off of Monte Carlo Tree Search for the Go board game, from scratch
A Monte Carlo Tree Search Library for users to apply to two-player games.
A Hex board game with a customizable Monte Carlo Tree Search (MCTS) agent with optional leaf parallelization in C++14. Includes a logging functionality for MCTS insights.
:sandwich: A tool to generate sandwich recipes for Pokémon Scarlet & Pokémon Violet
Cranes problem with Monte Carlo Tree Search algorithm
This repository contains the AI engine for a simplified version of Heartstone game
Work in Progress. Implementation of the Monte Carlo Tree Search, a decision making algorithm.
Reversi player using Monte Carlo Tree Search
Using reinforcement learning to play games.
In this project, my primary goal was to implement an AI player class powered by the Monte Carlo Tress Search algorithm which can play for a win as well as defend a defeat to compete with a Human player.