Well-Posedness of Singular Switched Explicit Models and Potential Applications in Model-Based Reinforcement Learning for Constrained Systems

Explore the mathematical foundations of singular switched explicit models and their applications in constrained systems through this 32-minute seminar lecture delivered by Dr. Sutrisno Sutrisno from Universitas Diponegoro. Examine the well-posedness properties of these complex mathematical models and discover their potential applications in model-based reinforcement learning for systems operating under constraints. Learn about the theoretical framework that underpins these models and understand how they can be leveraged to solve challenging problems in control theory and machine learning. Gain insights into the intersection of mathematical modeling, control systems, and artificial intelligence as presented at the Isaac Newton Institute's research programme on representing, calibrating, and leveraging prediction uncertainty from statistics to machine learning.