Show HN: Reinforcement learning tic-tac-toe in C, annotated (github.com)

A new project has emerged on Hacker News, presenting a C implementation of tic-tac-toe enhanced by reinforcement learning techniques. This project features a complete training loop that enables two AI agents to learn and optimize their gameplay. Users can engage with these AI opponents, choosing to play as either X or O. For those interested in the underlying mechanics, the code is annotated, and references Richard Sutton's foundational text on reinforcement learning, specifically pages 6-10 for an accessible introduction to the concepts. This development is significant for the AI/ML community as it not only demonstrates the practical application of reinforcement learning in a simple game, but also offers a hands-on opportunity for developers and researchers to explore and understand the intricacies of training AI agents. By utilizing a well-known game as a testing ground, the project highlights the potential of reinforcement learning algorithms to create autonomous systems that improve through experience, paving the way for more complex applications in various fields.