EquiLibre Technologies, a Prague-based AI lab founded by three ex-DeepMind researchers, is now valued at more than $500 ...

SummaryRFIC design is a complex “dark art” that limits progress in wireless technologies like 5G, autonomous vehicles, and ...

Introduction Efficient preventive management of acute exacerbation of chronic obstructive pulmonary disease (COPD) is ...

Perioperative anemia and red blood cell transfusions are important risk factors for morbidity and mortality in cardiac ...

This GitHub repository contains the code, data, and figures for the paper RAIN: Reinforcement Algorithms for Improving Numerical Weather and Climate Models. Also includes the SCBC and RCE experiments ...

While most reinforcement learning algorithms use two to five network layers, a research team achieved 2x to 50x performance gains by scaling network depth up to 1,024 layers in a self-supervised agent ...

Like humans, artificial intelligence learns by trial and error, but traditionally, it requires humans to set the ball rolling by designing the algorithms and rules that govern the learning process.

Abstract: Most reinforcement learning (RL) algorithms proposed to solve Nash equilibrium in multi-agent systems assume stable communication conditions or rely on accurate models of the environment.

Buildings are an important part of the energy consumption of cities. With recent developments in integrated energy systems in buildings, the need for a smart energy management system (EMS) has ...

These include such learning paradigms as Q-Learning and the Deep Q-Networks setups. Reinforcement Learning paradigms essentially aim at teaching robots to undertake certain actions that will be used ...