This depository involves four directions:
- The mathematical foundations of game-tree search and Markov decision processes (MDPs)
- Deep Q-learning for games
- CNN & RNN (Transform)
- Autoencoders, VAEs, GANs and Diffusion Models
Reinforcement Learning: An Introduction
Richard S. Sutton and Andrew G. Barto
Second Edition
MIT Press, Cambridge, MA, 2018
http://incompleteideas.net/book/the-book-2nd.html
Deep Learning - Adaptive Computation and Machine Learning series by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
https://github.com/HFTrader/DeepLearningBook
Artificial Intelligence: A Modern Approach
Stuart Russell, Peter Norvig
https://www.amazon.com/dp/9332543518/ref=cm_sw_r_tw_dp_U_x_rZufEbGBSJ2J7
Artificial Intelligence and Games
Georgios N. Yannakakis, Julian Togelius
https://link.springer.com/book/10.1007/978-3-319-63519-4
Artificial Intelligence for Computer Games
Pedro Antonio González-CaleroMarco Antonio Gómez-Martín
https://link.springer.com/book/10.1007/978-1-4419-8188-2
The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2017)
Authors: Trevor Hastie, Robert Tibshirani and Jerome Friedman
Free online https://web.stanford.edu/~hastie/ElemStatLearn/printings/ESLII_print12.pdf
GLHF:)