Semiconductor Engineering

Rethinking Robotics Reinforcement Learning: A Practical Humanoid Training Workflow

Reinforcement learning (RL) for robotics is often associated with large GPU clusters, distributed infrastructure, and x86-based development environments. Training a humanoid robot with high-fidelity ...
Scientific Research Publishing

The Grover Dilemma and Three Fundamental Barriers to Oracle-Based Quantum Search Algorithms ()

Department of Engineering Technology, Savannah State University, Savannah, GA, USA. Our analysis reveals that most claimed applications of Grover’s algorithm fall into one of several categories: Those ...
IEEE

Electrical Fault Diagnosis Method for Tunneling Equipment Based on Fault Simulation and Optimized Particle Swarm Algorithm

Abstract: To address the challenges of scarce training data and poor adaptability to dynamic working conditions in electrical fault diagnosis for tunneling equipment, this study proposes an ...
Wired

For Algorithms, Memory Is a Far More Powerful Resource Than Time

The original version of this story appeared in Quanta Magazine. One July afternoon in 2024, Ryan Williams set out to prove himself wrong. Two months had passed since he’d hit upon a startling ...
IEEE

The Study of Network Connectivity and Traffic Impact Based on Random Walk Algorithm and Monte Carlo Simulation

Abstract: This study analyzes the impacts on connectivity, stability, and traffic flow in urban transportation networks when critical infrastructure fails, using Random Walk algorithms and Monte Carlo ...
Quanta Magazine

For Algorithms, a Little Memory Outweighs a Lot of Time

One July afternoon in 2024, Ryan Williams set out to prove himself wrong. Two months had passed since he’d hit upon a startling discovery about the relationship between time and memory in computing.
Investopedia

Using Genetic Algorithms To Forecast Financial Markets

Samantha (Sam) Silberstein, CFP®, CSLP®, EA, is an experienced financial consultant. She has a demonstrated history of working in both institutional and retail environments, from broker-dealers to ...
Frontiers

A parallel heterogeneous policy deep reinforcement learning algorithm for bipedal walking motion design

Considering the dynamics and non-linear characteristics of biped robots, gait optimization is an extremely challenging task. To tackle this issue, a parallel heterogeneous policy Deep Reinforcement ...
Scientific Research Publishing

Multi-Strategy-Driven Salp Swarm Algorithm for Global Optimization ()

In response to the shortcomings of the Salp Swarm Algorithm (SSA) such as low convergence accuracy and slow convergence speed, a Multi-Strategy-Driven Salp Swarm Algorithm (MSD-SSA) was proposed.
Wired

I Asked an Algorithm to Optimize My Life. Here's What Happened

I was halfway through a master’s in Computer Science when my vision changed. I was working as a data scientist during my summer off from school, and I had friends who said things like “I’m at a local ...
PNAS

Distributed algorithms from arboreal ants for the shortest path problem

Evolution has led to natural algorithms that regulate collective behavior in many biological systems. Here, we investigate natural algorithms that solve the shortest path problem, a basic optimization ...
Frontiers

Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements

Snow is a crucial element in the Earth’s system, but snow depth and mass are very challenging to be measured globally. Here, we provide the theoretical foundation for deriving snow depth directly from ...