We propose a new measure of the cost of information structures in rational inattention problems, the "neighborhood-based" cost functions, given that many applications involve states with a topological structure. These cost functions summarize the results of a sequential information sampling...

We analyze a coordination game with information-constrained players. The players' actions are based on a noisy compressed representation of the game's payoffs in a particular case, where the compressed representation is a latent state learned by a variational autoencoder (VAE). Our generalized...

We derive a new cost of information in rational inattention problems, the neighborhood-based cost functions, starting from the observation that many settings involve exogenous states with a topological structure. These cost functions are uniformly posterior-separable and capture notions of...

We analyze a coordination game with information-constrained players. The players' actions are based on a noisy compressed representation of the game's payoffs in a particular case, where the compressed representation is a latent state learned by a variational autoencoder (VAE). Our generalized...