Control schemes that learn using measurement data collected online are increasingly promising for the control of complex and uncertain systems. However, in most approaches of this kind, learning is viewed as a side effect that passively improves control performance, e.g., by updating a model of the system dynamics. Determining how improvements in control performance due to learning can be actively exploited in the control synthesis is still an open research question. In this paper, we present AntLer, a design algorithm for learning-based control laws that anticipates learning, i.e., that takes the impact of future learning in uncertain dynamic settings explicitly into account. AntLer expresses system uncertainty using a non-parametric probabilistic model. Given a cost function that measures control performance, AntLer chooses the control parameters such that the expected cost of the closed-loop system is minimized approximately. We show that AntLer approximates an optimal solution arbitrarily accurately with probability one. Furthermore, we apply AntLer to a nonlinear system, which yields better results compared to the case where learning is not anticipated.

Build your first major project on Face Detection and Recognition model using Python, Machine Learning and Computer Vision library called OpenCV. In this course, you will build a model along with me from scratch.

Gabriel Guimaraes grew up in Vitória, Brazil, in a yellow house surrounded by star-fruit trees and chicken coops. His father, who wrote software for a local bank, instilled in him an interest in computers. On weekends, when Guimaraes got bored with Nintendo video games, he programmed his own. In grade school, he built a humanoid robot and wrote enough assembly code to make it zip around his home. In Vitória, an island city, his most ambitious peers dreamed of attending university in São Paulo, an hour away by plane.

Machine Learning, often called Artificial Intelligence or AI, is one of the most exciting areas of technology at the moment. New to machine learning and seeking ways to enhance your knowledge? Or maybe you work in an industry with artificial intelligence and need a machine learning course to position yourself for advancement? Either way, a machine learning Coursera course is worth considering. There are introductory courses to choose from if you're just getting started, or you can begin with intermediate or advanced options to level up your knowledge. Benzinga is here to help you find a course that fits your needs and busy lifestyle.

Benzinga Money is a reader-supported publication. We may earn a commission when you click on links in this article. New to machine learning and seeking ways to enhance your knowledge? Or maybe you work in an industry with artificial intelligence and need a machine learning course to position yourself for advancement? Either way, a machine learning Coursera course is worth considering.

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