Abstract: This paper presents a simulation-based benchmarking analysis of three reinforcement learning (RL) algorithms—Soft Actor-Critic (SAC), Deep Q-Network (DQN), and Proximal Policy Optimization ...
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 ...
School of Mechatronics and Automotive Engineering, Puyang Vocational and Technical College, Puyang, China Introduction: Parallel hybrid vehicles face challenges in real-time torque distribution, ...
This repository contains a detailed mindmap covering the fundamental concepts and advanced topics in Reinforcement Learning (RL). This mindmap was created as part of my personal learning journey to ...
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 solutions ...
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 challenge of navigating unmanned aerial vehicles (UAVs) can be effectively tackled through the application of reinforcement learning (RL) methodologies. Nonetheless, the baseline ...
A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and more useful. PROVIDENCE, R.I. [Brown University] — With the rise of 3D ...
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