Tag: Deep Reinforcement Learning

AI Machine Learning & Data Science Research

UC Berkeley’s FastRLAP Learns Aggressive and Effective High-Speed Driving Strategies With <20 Minutes of Real-World

In the new paper FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing, a UC Berkeley research team proposes FastRLAP (Fast Reinforcement Learning via Autonomous Practicing), a system that autonomously practices in the real world and learns aggressive maneuvers to enable effective high-speed driving.

AI Machine Learning & Data Science Research

DeepMind Trains AI Agents Capable of Robust Real-time Cultural Transmission Without Human Data

In the new paper Learning Robust Real-Time Cultural Transmission Without Human Data, a DeepMind research team proposes a procedure for training artificially intelligent agents capable of flexible, high-recall, robust real-time cultural transmission from human co-players in a rich 3D physical simulation without using human data in the training pipeline.

AI Machine Learning & Data Science Research

NVIDIA’s Isaac Gym: End-to-End GPU Accelerated Physics Simulation Expedites Robot Learning by 2-3 Orders of Magnitude

A Nvidia research team presents Isaac Gym — a high-performance robotics simulation platform that runs an end-to-end GPU accelerated training pipeline. Compared to conventional RL training methods that use a CPU-based simulator and GPU for neural networks, Isaac Gym achieves training speedups of 2-3 orders of magnitude on continuous control tasks.