Robots learn 1,000 tasks in one day from a single demo

Scientists achieve major robotics milestone as robot learns 1,000 different physical tasks in single day, potentially ...
Tech Xplore

Reinforcement learning accelerates model-free training of optical AI systems

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
Scientific Research Publishing

Wang, L. and Zhu, D. (2021) Tackling Ordinal Regression Problem for Heterogeneous Data: Sparse and Deep Multi-Task Learning Approaches. Data Mining and Knowledge Discovery, 35 ...

ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...
Frontiers

Museum game-based learning: innovative approaches from a constructivist perspective

Constructivist learning theory emphasizes the subjectivity, sociality, and contextuality of learning, promoting learning through the creation of problem situations and guiding learners to collaborate ...
IEEE

A Novel Multi-Task Learning-Based Approach to Multi-Energy System Load Forecasting

Abstract: Multi-Energy Systems (MES) allow optimal interactions between different energy sources. Accurate load forecasting for such intricate systems would greatly enhance the performance and ...
Scientific Research Publishing

Research on the Application of Task-Based Language Teaching in Integrated English Classroom Instruction ()

This study focuses on the application of Task-based Language Teaching (TBLT) in Integrated English classroom instruction. As a “learning by doing” language teaching method that emerged in the 1980s, ...
eSchool News

Lessons from an online teacher: Supporting phenomena-based learning

I have worked in many different states and in many different learning environments throughout my 19-year career as an educator. For the past 13 years I have been honored to teach at Agora Cyber ...
IEEE

Task Prioritization in Multiagent Environments: A Novel Approach Using Nash Q-Learning

Abstract: With the rapid proliferation of smartphones and various terminal devices, edge computing has gained increasing importance in overcoming computational limitations and enhancing service ...
Frontiers

HPRS: hierarchical potential-based reward shaping from task specifications

1 Cyber-Physical Systems Group, Computer Engineering, TU Wien, Vienna, Austria 2 Center for Digital Safety and Security, AIT Austrian Institute of Technology GmbH, Vienna, Austria The automatic ...