SOURCE-LINKED INTELLIGENCE

Simultaneous Forward and Inverse Human-in-the-Loop Optimization

arXiv · AI, language, vision and robotics · article · Sep 18, 2026 · UTC

Subjective user experience is important to human-robot interaction, but the outcomes users value, and how those preferences vary across individuals and contexts, are often unknown. While inverse learning approaches using human data can help identify user rewards, in many assistive settings the experimental costs of executing a control policy, measuring biomechanical or physiological outcomes, and collecting user feedback often limit the number of queries and optimization iterations. Here, we present Simultaneous Forward and Inverse Human-In-the-Loop Optimization (SFIHILO), which efficiently in

Read original source ↗ Open in workspace

recordType

paper

region

Global