Artificial Intelligence Planning - Uncertainty is Inevitable
Nils Jansen, Ruhr-University Bochum, Germany
Tuesday March 26, 2024
3:30 – 5PM; POB 6.304
Abstract
In this seminar, we discuss various aspects of artificial intelligence (AI) planning. Our mission is to devise a plan for a robust, resilient, and provably correct autonomous system under real-world conditions. For example, reinforcement learning promises that autonomous systems can learn to operate in unfamiliar environments with minimal human intervention. However, why haven't most autonomous systems implemented reinforcement learning yet? The answer is simple: there are significant unsolved challenges. One of the most important ones is obvious: Autonomous systems operate in unfamiliar, unknown environments. This lack of knowledge is called uncertainty. To tackle these challenges, we combine the areas of AI and Formal Methods and employ neurosymbolic AI methods to achieve trustworthy, reliable, and safe artificial intelligence.
Bio
Nils Jansen is a full professor at the Ruhr-University Bochum, Germany, and leads the chair of Artificial Intelligence and Formal Methods. The mission of his chair is to increase the trustworthiness of Artificial Intelligence (AI). Prof. Jansen is also an associate professor at Radboud University, Nijmegen, The Netherlands. He was a research associate at the University of Texas at Austin and received his Ph.D. with distinction from RWTH Aachen University, Germany. His research is on intelligent decision-making under uncertainty, focusing on formal reasoning about the safety and dependability of artificial intelligence (AI). He holds several grants in academic and industrial settings, including an ERC starting grant titled Data-Driven Verification and Learning Under Uncertainty (DEUCE).