Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
—The realistic performance of a multi-input multi-output (MIMO) communication system depends strongly on the spatial correlation properties introduced by clustering in the propag...
In this study we rethought efficient market hypothesis from a viewpoint of complexity of market participants’ prediction methods and market price’s dynamics, and examined the ...
We present the definition of diverse models of physical systems using the Cell-DEVS paradigm. Cell-DEVS is an extension of the DEVS formalism that allows the definition of cellula...
Javier Ameghino, Alejandro Troccoli, Gabriel A. Wa...
This paper introduces Perplexus, a European project that aims to develop a scalable hardware platform made of custom reconfigurable devices endowed with bio-inspired capabilities...