Abstract This paper presents an intuitive explanation about why and how Rawlsian Theory of Justice (Rawls in A theory justice, Harvard University Press, Harvard, 1971) provides the foundations to a solution for algorithmic bias. The contribution is discuss show ideas their original form (e.g. veil ignorance , position allowing inequalities that serve worst-off) are relevant operationalize fairn...

We present a self-supervised method to disentangle factors of variation in high-dimensional data that does not rely on prior knowledge the underlying profile (e.g., no assumptions number or distribution individual latent variables be extracted). In this which we call NashAE, feature disentanglement is accomplished low-dimensional space standard autoencoder (AE) by promoting discrepancy between ...

Qualitative decision tools have been used in AI and CS in various contexts, but their adequacyis still unclear. To examine this question, our work employs the axiomatic approach to characterize the properties of various decision rules. In the past, we presented a constructive representation theorem for the maximin decision criterion, and we characterized conditions under which an agent can be v...

In this paper we extend the classical min-max model predictive control framework to a class of uncertain discrete event systems that can be modeled using the operations maximization, minimization, addition and scalar multiplication, and that we call max-min-plus-scaling (MMPS) systems. Provided that the stage cost is an MMPS expression and considering only linear input constraints then the open...