4 accepted papers
Large Language Models (LLMs) excel in reasoning and generation across domains, but still struggle with identifying and diagnosing complex errors. This stems mainly from training objectives that prioritize correct answers, limiting exposure to and learning from errors. While recent studies have begun
In the evolving artificial intelligence domain, hybrid human-machine systems have emerged as a transformative research area. While many studies have concentrated on individual human-machine interactions, there is a lack of focus on multi-human and multi-machine dynamics. This paper delves into these…
We investigate a variation of the art gallery problem in which a team of mobile guards tries to track an unpredictable intruder in a simply-connected polygonal environment. The guards are confined to move along the diagonals of a polygon, and are deployed according to the strategy proposed in [1] th…
In this letter, we address a visibility-based target-tracking problem in which a mobile observer tries to track a mobile target for a finite time. In order to ensure tracking guarantees for the observer, we formulate the problem as a finite-horizon zero-sum game between the observer and the target.