Daniel Dantas

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Gittins tried to cast the problem in the most general form he could: multiple options to pursue, a different probability of reward for each option, and a certain amount of effort (or money, or time) to be allocated among them. It was, of course, another incarnation of the multi-armed bandit problem.
Algorithms to Live By: The Computer Science of Human Decisions
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