policy
Tic-Tac-Toe-game-using-Reinforcement-Learning-with-Q-Learning-Agent
manjul-mayank · PyTorch
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Overview
Name
Tic-Tac-Toe-game-using-Reinforcement-Learning-with-Q-Learning-Agent
Author
manjul-mayank
Framework
PyTorch
License
MIT
Skill type
other
Evidence level
untested
Task description
This project implements a reinforcement learning (RL) agent that learns to play the classic Tic-Tac-Toe game. It uses a simple value-based approach to learn optimal moves through self-play. The project is implemented in Python using Jupyter Notebook and provides a great foundation for understanding
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
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Datasets that reference this policy
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