Internationaler Workshop unter Leitung von Dr. Karolina Krzyżanowska und Prof. Dr. Stephan Hartmann (CAS Senior Researcher in Residence).
02.02.2017 – 03.02.2017
Indicative conditionals, that is sentences of the form "If A, B" play an important role in our everyday and scientific reasoning as well as in argumentation, decision-making, and planning. It therefore should not come as a surprise that a lot of what we learn is conditional in form. What might come as a surprise, however, is that it is not entirely clear what learning a piece of conditional information amounts to. How do people adjust their beliefs upon learning a conditional? And how should a rational agent accommodate a new piece of conditional information? Finally, what are the desiderata that a descriptively correct theory of learning from conditionals should satisfy? Some attempts at answering these and related questions have been made, both within the tradition of qualitative belief revision and in Bayesian epistemology. It remains to be seen, however, whether any of the available models of learning fits all our intuitions and if they make correct, empirical predictions. This interdisciplinary workshop brings together philosophers, logicians, and psychologists interested in reasoning and argumentation, allowing them to share their unique perspectives and to discuss both descriptive and normative answers to these questions.
Sprecher/innen: Peter Collins (Birkbeck), Benjamin Eva (LMU), Estefania Gazzo (Gießen), Mario Günther (LMU), Ulrike Hahn (Birkbeck und LMU), Stephan Hartmann (LMU), Gabriele Kern-Isberner (Dortmund/CAS Visiting Fellow), Karolina Krzyżanowska (LMU), Mike Oaksford (Birkbeck), David Over (Durham/ CAS Visiting Fellow), Henrik Singmann (Zürich)
Ort und Anmeldung
CAS, Seestraße 13, 80802 München
Für die Teilnahme ist eine Anmeldung erforderlich. Wenn Sie Interesse an unserer Veranstaltung haben, bitten wir Sie sich 25. Januar mit uns bis in Verbindung zu setzen:
- Abstracts "Learning Conditionals" (248 KByte)
- Program "Learning Conditionals" (353 KByte)
- Presentations "Learning Conditionals" (8 MByte)