In this tutorial, we shift from traditional prompt crafting to a more systematic, programmable approach by treating prompts as tunable parameters rather than static text. Instead of guessing which ...

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 ...

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 ...

1 Department of Quantitative Methods, College of Business, King Faisal University, Al-Ahsa, Saudi Arabia 2 Department of Quantitative Methods, University of Sousse, Sousse, Tunisia Humanitarian aid ...

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 ...

Abstract: Most renewable energy power systems are created to provide more resilient, reliable, economical, sustainable and secure power support services for loads. However, owing to the inherent ...