IEEE

Differentiable Weights-Varying Nonlinear MPC via Gradient-Based Policy Learning: An Autonomous Vehicle Guidance Example

Abstract: Tuning Model Predictive Control (MPC) cost weights for multiple, competing objectives is labor-intensive. Derivative-free automated methods, such as Bayesian Optimization, reduce manual ...
IEEE

Human-in-the-loop Learning for Adaptive Robot Manipulation using Large Language Models and Behavior Trees

Abstract: Large Language Models (LLMs) are now transforming the way robots learn to work in unpredictable environments, such as homes or small enterprises. A growing number of approaches are combining ...
MIT Technology Review

Why having “humans in the loop” in an AI war is an illusion

We don't really understand AI's inner workings, so we're effectively flying blind. The availability of artificial intelligence for use in warfare is at the center of a legal battle between Anthropic ...
Journal of Medical Internet Research

Predicting the Risk of Sleep Disorders Using a Machine Learning–Based Simple Questionnaire: Development and Validation Study

We applied extreme gradient boosting using selected features to develop a simple questionnaire predicting sleep disorders (SLEEPS). The accuracy of the algorithm was evaluated using the area under the ...