IEEE

Deep Reinforcement Learning with Graph Neural Networks: An Indepth Analysis of Algorithms and Applications

Abstract: Deep Reinforcement Learning (DRL) enable several areas of artificial intelligence, including perception recognition, expert system, recommender program and game. Also, graph neural networks ...
WDWMAGIC

Inside Disney's Self-Walking Olaf: New Research Details How the Robot Character Works

DisneyResearchHub has published a detailed technical paper outlining how Walt Disney Imagineering Research & Development ...
Tech Xplore on MSN

AI-powered robotic hands learn dexterity by mimicking human movements and anatomy

Step inside the Soft Robotics Lab at ETH Zurich, and you find yourself in a space that is part children's nursery, part ...
IEEE

Drone Landing and Reinforcement Learning: State-of-Art, Challenges and Opportunities

Abstract: Unmanned aerial vehicles, and special multirotor drones, have shown great relevance in a plethora of missions that require high affordance, field of view, and precision. Their limited ...

New model frames human reinforcement learning in the context of memory and habits

Humans and most other animals are known to be strongly driven by expected rewards or adverse consequences. The process of ...
GitHub

Pearl - A Production-ready Reinforcement Learning AI Agent Library

Pearl is a new production-ready Reinforcement Learning AI agent library open-sourced by the Applied Reinforcement Learning team at Meta. Furthering our efforts on open AI innovation, Pearl enables ...
GitHub

verl: Volcano Engine Reinforcement Learning for LLMs

verl is a flexible, efficient and production-ready RL training library for large language models (LLMs). verl is the open-source version of HybridFlow: A Flexible and Efficient RLHF Framework paper.