Unsupervised and reinforcement learning in neural networks
نویسندگان
چکیده
2.3. Initialize both Q-values at 2 (optimistic). Assume that, as in in the first part, in the first round you get for both actions the reward. Update your Q values once with η = 0.2. Suppose now that in the following rounds, you choose actions a1 and a2 alternatingly and update the Q-values with a very small learning rate (η = 0.001). How many rounds does it take on average, until the maximal Q-value also reflects the best action? (Hint: Transform the discrete online update rule for the two Q-values into differential equations for the expected Q-values after each time step.)
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