By using reinforcement learning, researchers train virtual agent to determine the best time to administer medication based on ...

A machine-learning-enhanced approach to chemical analysis is drastically expanding the chemical record of life on Earth, and ...

Determining the least expensive path for a new subway line underneath a metropolis like New York City is a colossal planning challenge—involving thousands of potential routes through hundreds of city ...

It’s useful to think of our engagement with algorithms as a social contract. Political theorists have long used the social contract as a device to explain why individuals submit to the authority of a ...

Jim Simons’s Medallion Fund averaged 66% annual returns for three decades, using math that would make ChatGPT weep.

There are more candidates on the waitlist for a liver transplant than there are available organs, yet about half the time a ...

A machine learning-based model predicts how long it will take an organ donor to die after removing life support, aiding surgeons in deciding whether organs can be successfully transplanted.

Abstract: In the era of large-scale machine learning, large-scale clusters are extensively used for data processing jobs. However, the state-of-the-art heuristic-based and Deep Reinforcement Learning ...

Abstract: This article proposes online data-based reinforcement learning (RL) algorithm for adaptive output consensus control of heterogeneous multiagent systems (MASs) with unknown dynamics. First, ...

An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...