The problemof choosing an optimal toolkit day after day,when there is uncertainty concerning the value of different tools that can only be resolved by carrying the tools, is a multi-armed bandit problem with nonindependent arms. Accordingly, except for very simple specifications, this...

A decision maker faces an unobserved state of nature. She updates her prior on the state based on the realizations of a signal. In this note, we show that the expected posterior on any given state, taking expectation under the conditional distribution of the signal on this same state, is never...

Many choice-theoretic and game-theoretic applications in Economics invoke some form of supermodularity or increasing differences for objective functions defined on lattices. These notes provide axiomatic foundations for these properties on expected-utility representations of preferences over...

In standard experimentation problems, decision makers are allowed to experiment on at most one project at a time. Would it ever be beneficial to experiment on more than one project simultaneously if we let them? We show that the answer is Yes, even if it is known that only one of the projects is...

The problem of choosing an optimal toolkit day after day, when the distribution of values of different toolkits is uncertain and can only be observed by carrying different toolkits, is a multi-armed bandit problem with non-independent arms. Accordingly, except for very simple specifications,...

This paper continues our study of heuristics employed to choose dynamically tools to put in a toolkit, where the value of any tool can be discovered only by choosing it. This is a multi-armed bandit problem with “arms” that are not independent, hence it is a problem for which the optimal...