ml-agents and Self-Play-TicTacToe-AI-ML-Agents-
ML-Agents is a foundational reinforcement learning framework that Self-Play-TicTacToe-AI uses as its core dependency to implement a specific game-playing agent, making them ecosystem siblings where one is the general-purpose toolkit and the other is an example application built on top of it.
About ml-agents
Unity-Technologies/ml-agents
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
This toolkit helps game developers and researchers create intelligent characters and systems within Unity games and simulations. You provide a Unity game environment, and the toolkit outputs trained AI agents that can control Non-Player Characters (NPCs), automate game testing, or evaluate design choices. Game developers and AI researchers are the primary users.
About Self-Play-TicTacToe-AI-ML-Agents-
Sebastian-Schuchmann/Self-Play-TicTacToe-AI-ML-Agents-
A Self Play reinforcement learning Agent learns to play TicTacToe using the ML-Agents Framework in Unity.
This helps Unity game developers create and train an AI agent to play TicTacToe using self-play reinforcement learning. You provide the Unity environment with the TicTacToe game logic, and it outputs a trained AI model capable of playing the game. This is ideal for game developers or AI enthusiasts looking to implement game AI within the Unity engine.
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