IEEE

Deep Reinforcement Learning-Based Motion Planning and PDE Control for Flexible Manipulators

Abstract: This article presents a motion planning and control framework for flexible robotic manipulators, integrating deep reinforcement learning (DRL) with a nonlinear partial differential equation ...
Tech Xplore

Geometry behind how AI agents learn revealed

A new study from the University at Albany shows that artificial intelligence systems may organize information in far more ...
InfoQ

Google BigQuery Adds SQL-Native Managed Inference for Hugging Face Models

Google has launched SQL-native managed inference for 180,000+ Hugging Face models in BigQuery. The preview release collapses the ML lifecycle into a unified SQL interface, eliminating the need for ...
Frontiers

Solving robotics tasks with prior demonstration via exploration-efficient deep reinforcement learning

This paper proposes an exploration-efficient deep reinforcement learning with reference (DRLR) policy framework for learning robotics tasks incorporating demonstrations. The DRLR framework is ...
Frontiers

LG-H-PPO: offline hierarchical PPO for robot path planning on a latent graph

The path planning capability of autonomous robots in complex environments is crucial for their widespread application in the real world. However, long-term decision-making and sparse reward signals ...
IEEE

SA-MARL: Novel Self-Attention-Based Multi-Agent Reinforcement Learning With Stochastic Gradient Descent

Abstract: In the rapidly advancing Reinforcement Learning (RL) field, Multi-Agent Reinforcement Learning (MARL) has emerged as a key player in solving complex real-world challenges. A pivotal ...