In recent years, hand gesture recognition (HGR) technologies that use electromyography (EMG) signals have been of considerable interest in developing human–machine interfaces. Most state-of-the-art HGR approaches are based ...

This work presents two Deep Reinforcement Learning (Deep-RL) approaches to enhance the problem of mapless navigation for a terrestrial mobile robot. The methodology focus on comparing a Deep-RL technique based on the Deep ...

The aim of this paper is to develop an AI agent with self-learning capabilities that is able to play classical Atari console games without human intervention and achieve next to human level performance. In order to achieve ...

It is necessary, for the best oil production, the constant development of new alternatives for the exploitation of the fields. The need to optimize the factors involved in this process requires great care in all the ...

The increased sophistication of mobile networks such as 5G and beyond, and the plethora of devices and novel use cases to be supported by these networks, make of the already complex problem of resource allocation in wireless ...

Reinforcement learning emerged in the 1980s and is one of three main areas of machine learning, the other two being supervised and unsupervised learning. Reinforcement problems have unique characteristics, such as the ...