Abstract: Satellite-terrestrial integrated networks (STINs) require a robust handover mechanism to ensure reliable mobility management and load balancing. However, many studies still focus on ...

Discover how Group Relative Policy Optimization (GRPO) works with a clear breakdown of the core formula and working Python code. Perfect for those diving into advanced reinforcement learning ...

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 ...

ABSTRACT: Maritime transportation is increasingly being subjected to pressure to balance economic efficiency with environmental sustainability under regulatory frameworks such as global trade demands ...

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: This paper introduces a Proximal Policy Optimization (PPO)-based virtual impedance (VI) controller to enhance both power sharing and system response under disturbances in inverter-interfaced ...

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.