A different implementation for car rental problem #166
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By saving probability models in numpy array, the DP algorithm could be very efficient without manually parallel computing.
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By saving probability models in numpy array, the DP algorithm could be very efficient without manually parallel computing.
The running time is short and it's about 2 seconds to generate the plots in the book.
The idea is to separate reward and value in Bellman equation and calculate their expected terms separately. Since we have the model in DP problem, we can save the expected reward and probability of state transitions before policy updating.