705850 Quantum computing, control and learning
summer semester 2016 | Last update: 08.05.2019 | Place course on memo listBuilding on a basic understanding of quantum information and computation this course will first provide an overview of selected established concepts and methods of computation, learning and artificial intelligence. As its main goal the course will explore the connections to quantum systems with an emphasis on learning and self-adaption.
-- projective simulation -- reinforcement learning -- learning classifier systems -- neural networks -- ...
The course will consist of lectures and predominantly of talks contributed by the course participants on selected research articles or book chapters.
-- Stuart Russell, Peter Norvig: "Artificial Intelligence: A Modern Approach", 3rd. Ed., Prentice Hall (2009) (see also http://aima.cs.berkeley.edu/) -- Richard S. Sutton, Andrew G. Barto: "Reinforcement Learning: An Introduction", MIT Press (Cambridge, USA, 1998) (see also http://webdocs.cs.ualberta.ca/~sutton/book/the-book.html) -- Dario Floreano, Claudio Mattiussi: "Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies", MIT Press (USA, 2008) (see also: http://baibook.epfl.ch/)