Abstract: This paper introduces a novel adaptive path tracking controller that integrates the Proximal Policy Optimization (PPO) algorithm with a Proportional-Integral-Derivative (PID) control ...

In this tutorial, we implement an end-to-end Direct Preference Optimization workflow to align a large language model with human preferences without using a reward model. We combine TRL’s DPOTrainer ...

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 ...

Introduction: The current US adult heart allocation policy has several limitations, including being heavily focused on device utilization rather than individual patient illness severity, high number ...

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: 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 ...

A modular, cross-platform Proximal Policy Optimization (PPO) implementation that can be integrated into JavaScript SPAs, Node.js apps, Unity 3D games, Python applications, and more. The system uses a ...

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.

ABSTRACT: The growing demand for energy-efficient Wireless Sensor Networks (WSNs) in applications such as IoT, environmental monitoring, and smart cities has sparked exhaustive research into practical ...