Bibliography (49):

  1. ​ Problem 14 Dynamic Programming Solutions

  2. Rational Decision-Making Under Uncertainty: Observed Betting Patterns on a Biased Coin

  3. Openai/gym: A Toolkit for Developing and Comparing Reinforcement Learning Algorithms.

  4. memoise

  5. Faster Hash Maps in R

  6. Array-Memoize: Memoization Combinators Using Arrays for Finite Sub-Domains of Functions

  7. Vector: Efficient Arrays

  8. https://github.com/FeepingCreature

  9. KC Exact Solution

  10. https://x.com/ArthurB/status/823241996244422656

  11. Repoze.lru: Tiny LRU Cache

  12. Apache MXNet

  13. Meta-learning of Sequential Strategies

  14. Deep Reinforcement Learning for Keras

  15. Keras: Deep Learning for Humans

  16. TensorFlow

  17. Maxpumperla/hyperas: Keras + Hyperopt: A Very Simple Wrapper for Convenient Hyperparameter Optimization

  18. Hyperopt Documentation

  19. Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms

  20. Playing Atari with Deep Reinforcement Learning

  21. Deep DPG (DDPG): Continuous control with deep reinforcement learning

  22. Keras-Rl/examples/dqn_cartpole.py at Master

  23. Deep Reinforcement Learning: Pong from Pixels

  24. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

  25. Keras-Rl/examples/ddpg_pendulum.py at Master

  26. The Gambler’s Problem and Beyond