Artificial Intelligence (AI) has achieved remarkable successes in recent years. It can defeat human champions in games like Go, predict protein structures with high accuracy, and perform complex tasks ...

Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...

With its playlist chatbot, Spotify says you could ‘curate your next Discover Weekly, exactly the way you want it.’ With its playlist chatbot, Spotify says you could ‘curate your next Discover Weekly ...

The rapid growth of AI is projected to push global data center power demand to 2,200 terawatt-hours (TWh) by 2030, an "always-on" load that threatens to overwhelm the world's aging electrical grids.

Abstract: This research presents an ensemble Reinforcement Learning (RL) approach that combines Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) algorithms to tackle quantum control ...

Researchers at the University of Science and Technology of China have developed a new reinforcement learning (RL) framework that helps train large language models (LLMs) for complex agentic tasks ...

0267_RL_for_resource_allocation/ ├── src/ # Source code │ ├── agents/ # RL agents implementation │ │ ├── __init__.py │ │ └── agents ...

This project implements an intelligent traffic signal controller using Proximal Policy Optimization (PPO), a state-of-the-art deep reinforcement learning algorithm. The system intelligently manages ...

The new quantum computing algorithm, called "Quantum Echoes," is the first that can be independently verified by running it on another quantum computer. When you purchase through links on our site, we ...