Training a Chess Engine Using Reinforcement Learning (First RL Project)

I am on the verge of completing my undergraduate degree in AI/ML. I have worked on deep learning, LLMs, and transformers, but this is my first project involving reinforcement learning.

I want to train a chess engine using reinforcement learning on my MacBook M2. I have researched some common strategies that are typically used.

My idea is to take two models (possibly neural networks) and have them play against each other while learning through reinforcement learning techniques.

Once they have learned the basics of chess or reached a plateau during training, I plan to reinforce both models individually using some unique game strategies. After they learn these strategies, I will pit them against each other again. I believe this approach could help them learn faster and develop counter-strategies, because initially they are similar, but after individual training they become distinct.

I would love it if some of you could recommend papers or strategies that I could use, and also share your suggestions on this approach.