Teaching

Winter Term 2017 (CONCEPT—University of Cologne)
    • Introduction to Formal Epistemology
      In this course I will introduce the main topics and methods of the research field known as ‘formal epistemology’. We will see how modal logic can be used as a means of encoding epistemic principles of knowledge and belief, and apply it to the treatment of paradoxes such as the Knowability Paradox and Moore's Paradox. We will also go through the literature on Bayesianism, thus bringing the probability calculus to bear on epistemological issues, such as the problem of apparently rational but inconsistent beliefs and the relationship between categorical beliefs and degrees-of-belief. Reading materials accessible here.

    • Modal knowledge, imagination and reason
      We can not only have knowledge of how things are in the world—but also of how they could be or how they must be. But how do we know what is possible and what is necessary? Knowledge of necessity is not gained by means of perceptual experience, as it was emphasized by Immanuel Kant. And sometimes we gain knowledge of what is possible even though experience does not present us with the relevant possible scenarios. If it is not experience that teaches us what is possible and what is necessary, what does? In this course, we will look into the literature on imagination as a guide to possibility, modal knowledge through suppositional reasoning  and problems with the notion of rational insight or intuition as a means of knowing necessary truths. Reading materials accessible here.
    Summer Term 2017 (MCMP)
      • Philosophy of Artificial Intelligence (B.A./M.A.).
        In this seminar we are going to explore some philosophical questions about the field of Artificial Intelligence. We will start by reviewing the first attempts to automate theorem-proving techniques (in the 50s and 60s) and the frustrated use of those results to emulate intelligence/rationality in general. Next we analyze the use of neural networks to compute several types of functions and the connectionist paradigm in cognitive psychology/AI. Finally, we will discuss the miscellaneous toolbox that is available to Artificial Intelligence practitioners nowadays—most importantly, machine learning techniques—with an eye to answering the question whether we are any way nearer to successfully simulating rational or intelligent agents.
      Winter Term 2016/17 (MCMP)
      • The A Priori (B.A./M.A. Seminar). Syllabus attached below.
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