Rafael R. Souza

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Mean field games is a recent area of study introduced by Lions and Lasry in a series of seminal papers in 2006. Mean field games model situations of competition between large number of rational agents that play non-cooperative dynamic games under certain symmetry assumptions. A key step is to develop a mean field model, in a similar way to what is done in(More)
Negative Entropy, Zero temperature and stationary Markov chains on the interval. Abstract We analyze properties of maximizing stationary Markov probabilities on the Bernoulli space [0, 1] N , which means we consider stationary Markov chains with state space given by the interval S = [0, 1]. More precisely, we consider ergodic optimization for a continuous(More)
We analyze some properties of maximizing stationary Markov probabilities on the (modified) Bernoulli space [0, 1] N , which means we consider stationary Markov chains with state space S = [0, 1]. More precisely, we consider ergodic optimization for a continuous potential A, where A : [0, 1] N → R which depends only on the two first coordinates of [0, 1] N.(More)
Sting_RDB is a relational database composed of structural parameters for protein analysis operating with a collection of both publicly available data (e. consolidated and integrated into Sting_RDB makes this database one of the most comprehensive databases available for analysis of protein structure and sequence. The main features of Sting database can be(More)
The recommendation systems aim to minimize information overload by helping user's in searching desired information. Faced with this scenario, we investigate the use of cloud factors able to have a positive influence on generating recommendations. Thus, we present a new, simple model based on cloud features which is associated with the content-based(More)
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