Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

In this study, we focus on investigating a nonsmooth convex optimization problem involving the l 1-norm under a non-negative constraint, with the goal of developing an inverse-problem solver for image ...

In tactical communication networks, highly dynamic topologies and frequent data exchanges create complex spatiotemporal dependencies among link states. However, most existing intelligent routing ...

This project presents a comprehensive overview of building a simulation environment in Unity and applying the Proximal Policy Optimization (PPO) algorithm from Unity’s built-in ML-Agents toolkit. We ...

Goal-reaching simulation in Unity by combining to use ML-Agents toolkit and Anaconda involves training an agent to navigate and interact with environments to reach predefined goal target. This task ...

Reinforcement learning (RL) plays a crucial role in scaling language models, enabling them to solve complex tasks such as competition-level mathematics and programming through deeper reasoning.

Rasner Media CEO Reid Rasner on Thursday announced that he would no longer seek a bid to purchase the controversial social media app TikTok, citing concerns about national security in regards to China ...

ABSTRACT: This study introduces a novel simulation-based framework that integrates Agent-Based Modelling (ABM) with Reinforcement Learning (RL) to evaluate and optimize policies for mental health ...

ABSTRACT: In the field of machine learning, support vector machine (SVM) is popular for its powerful performance in classification tasks. However, this method could be adversely affected by data ...