Your own AI story - A different story adventure where there is infinite possibilities, you choose what you do in your story, and AI decides what happens to your story next.

A drop-in StateTree-based AI plugin for Unreal Engine 5. Provides a complete NPC behavior loop — perception, target tracking, navigation, and combat — driven entirely by StateTree global tasks, state tasks, and conditions.

「17歩」麻雀AIの研究開発リポジトリ。ログ解析から教師あり学習までのパイプラインを実装。

A DOOM-inspired AI token system designed to manage multi-enemy combat experiences in games.

Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials. Reinforcement Learning for Game Playing Agents enables AI agents to learn optimal game strategies through trial and error, improving performance, adaptability, and decision-making in gaming environments.

Connect 4 AI using minimax, heuristics, and machine learning

This Python project implements a classic Tic Tac Toe game using object-oriented programming principles. The game provides a console-based interface where players can take turns against an AI opponent.

AlphaZeroをベースにした五目並べAI。深層強化学習の学習・研究導入として実装。

A project on custom MLP controlling a 2D lander game (Python + Pygame, data-driven training, MATLAB RMSE analysis).

This project is a reference implementation of the method proposed in the paper "Mastering Othello with genetic algorithm and reinforcement learning".

A Reinforcement Learning project showcasing an AI agent that dynamically adapts its in-game persona (e.g., aggressive, evasive) based on real-time player behavior, creating a more personalized and engaging gaming experience.

Develop a 3D interactive graphics rendering engine

Here is a Rule-based AI for playing tic-tac-toe using strategic decision-making.

fork form behavior3ts but support async/await natrually

Created in Unity 5 for the purposes of learning AI techniques. Features behaviour trees and A* pathfinding.

A real-time Mario game-playing AI built on a custom Deep Q-Network.

A Sudoku game with an AI agent that generates puzzles, solves them, and verifies their validity using constraint satisfaction algorithms. The AI uses backtracking and heuristics for efficient solving. It also offers a web interface for users to interact with the puzzle.

This repo is a live list of papers on game playing and large multimodality model - "A Survey on Game Playing Agents and Large Models: Methods, Applications, and Challenges".

Domain model for Hierarchical Task Network Planning (HTN) implemented in Unity C#