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UCB, Thompson sampling etc seems myopic/greedy for bandits?

The (binary) multi-armed bandit actually is a MDP with one state and $K$ actions. So your suggestion boils down to meta-learning: Find the parameters of one MDP that can solve another. Let's go with ...
maxy's user avatar
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1 vote

Markov Decision Processes Model

you have in front of you 10 slot machines you can play with any of them, and each of them have a specific winrate (reward function) the only state of this MDP is the initial state, the one where you ...
Alberto's user avatar
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