BaGBeM Research Workshop "Behavioral Principles of Decision Making in Complex Intertemporal Problems"
Date: 20.- 22. November 2019
Instructors: Dr. Martin Hohnisch, Dr. Sabine Pittnauer
Room: F21/02.24
Topics
- Decision making under uncertainty
- Dynamic decision making
- Learning, heuristics, and Bounded Rationality
- Evolution of “Technologies of Rationality”
- Self-design of cognitive procedures by decision makers
- Non-paternalistic procedural interventions to enhance decision making
About the instructors
Martin Hohnisch and Sabine Pittnauer are Visiting Fellows at the Israel Institute of Technology (Technion) in Haifa. Between 2006 and 2015, they worked under the supervision of Professor Reinhard Selten at the position "Rationalität im Lichte der Experimentellen Wirtschaftsforschung” at the University of Bonn. Research academic work, together with Reinhard Selten, has been pusblished in journals such as Organization Science, Journal of Economic Behavior and Organization and Journal of Behavioral Decision Making. Previously, they worked in the field of agent-based simulation of economic systems. Their research interests include the understanding of decision-making in complex problems, as well as the connection of behavioral and agent-based approaches in the modeling of economic systems. Martin Hohnisch holds a PhD from the University of Bamberg, while Sabine Pittnauer from the University of Bonn.
Schedule
Wednesday, 20. November
15:00 – 17:00 – Introduction to complex decision making and a live decision-making experience
Thursday, 21. November
10:00 – 11:30 – Cognitive resources and exploration versus exploitation of technologies of rationality
14:00 – 15:30 – Architecture of cognitive procedures and cognitive design
16:30 – 18:30 – Live decision-making experience in a complex dynamic decision problem
Friday, 22. November
10:00 – 11:30 – Learning procedures as a design problem
14:00 – 15:30 – Learning from the decisions of others
16:00 – 17:00 – Summary of theoretical findings and discussion of research avenues for an integration of agent-based and behavioral modeling