IEEE

RadDQN: A Deep Q Learning-Based Architecture for Finding Time-Efficient Minimum Radiation Exposure Pathway

Abstract: Recent advances in deep reinforcement learning (DRL) have expanded its use in various automation sectors, including the nuclear industry. While DRL shows promise for optimizing radiation ...
The New York Times

These Three Red States Are the Best Hope in Schooling

Students at an elementary school in Hollandale, Miss.Credit... Supported by By Nicholas Kristof Photographs by Lynsey Addario Mr. Kristof is an Opinion Columnist who reported from Alabama and ...
IEEE

Deep Q-Learning with Gradient Target Tracking

Abstract: This paper introduces Q-learning with gradient target tracking, a novel reinforcement learning framework that provides a learned continuous target update mechanism as an alternative to the ...
Gizmodo

NASA’s Artemis 2 Will Test Human Health in Deep Space Like Never Before

The Artemis 2 astronauts will venture deeper into space than any human has gone before. That presents some seriously exciting research opportunities. Reading time 5 minutes The human body is a complex ...
marktechpost

A Coding Implementation to Train Safety-Critical Reinforcement Learning Agents Offline Using Conservative Q-Learning with d3rlpy and Fixed Historical Data

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...