Solving the Gambler's Problem using Value Iteration from the book Reinforcement Learning (2nd Edition) by Richard S. Sutton and Andre G. Barto
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Nov 29, 2019  - Python
 
Solving the Gambler's Problem using Value Iteration from the book Reinforcement Learning (2nd Edition) by Richard S. Sutton and Andre G. Barto
A simulation of the gambler's ruin problem: the traditional set-up with 2 players, as well as a general solution in n players.
multi-armed bandit, gambler problem, cliff problem and TD learning
Gambler's problem environment implemented OpenAI gym-style
python code successfullly reproduce the Gambler problem, Figure 4.6 of Chapter 4 on Sutton's book, Sutton, R. S., & Barto, A. G. (1998). Reinforcement learning: An introduction (Vol. 1, No. 1). Cambridge: MIT press.
A dynamic programming solution to the classic gambler's problem introduced in Sutton and Barton's RL book
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