Modern air defense confrontations demand rapid, precise task assignments in environments where threats evolve within seconds.

Abstract: With the development of sixth-generation (6G) wireless communication networks, the security challenges are becoming increasingly prominent, especially for mobile users (MUs). As a promising ...

The grey wolf optimization algorithm is a metaheuristic optimization algorithm based on the behavior of grey wolf groups in nature, which has the advantages of a simple concept and few adjustment ...

If it feels like social platforms suddenly “get” you more than they used to, you’re not imagining it! In 2026, feeds aren’t only reacting to what you click anymore. They’re predicting what you ...

I’ve been working on a deep reinforcement learning project that pushed me into one of the most challenging control environments I’ve ever experimented with - a 2D kart racing simulator built from ...

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 ...

Abstract: With the rapid advancement of electric vehicles and the widespread integration of artificial intelligence technology, the demands for enhanced comfort and stability in vehicle suspension ...

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 ...

Reinforcement learning (RL) has witnessed tremendous advances in recent years, enabling agents to master tasks ranging from video games to robotics. However, designing stable, sample-efficient ...

This study introduces a novel metaheuristic optimization algorithm named Logarithmic Mean-Based Optimization (LMO), designed to enhance convergence speed and global optimality in complex energy ...