The dynamic motion primitive-based (DMP) method is effective for learning from demonstrations. However, most current DMP-based methods focus on learning one task with one module. Although, some deep ...

Error-based and reward-based mechanisms of motor learning co-occur in real-world scenarios but are traditionally isolated in laboratory tasks via feedback manipulations. We examined the ...

Most robot headlines follow a familiar script: a machine masters one narrow trick in a controlled lab, then comes the bold promise that everything is about to change. I usually tune those stories out.

Discover how learning curves enhance productivity by reducing time and costs per task as proficiency improves, impacting ...

Continual robot learning is an emerging interdisciplinary field that integrates advances from machine learning, robotics, and cognitive science to build ...

Human vs. AI: A comparative effectiveness study of large language models for automated biomarker extraction. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does ...