Universität Wien

040820 UK Theories of Bounded Rationality (BA) (2016W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

http://homepage.univie.ac.at/karl.schlag/
Office hours: Thursday 11.30-12.15 or by appointment

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 50 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Thursday 06.10. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Thursday 13.10. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Thursday 20.10. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Thursday 27.10. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Friday 11.11. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Thursday 17.11. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Thursday 24.11. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Friday 09.12. 09:45 - 13:00 Hörsaal 12 Oskar-Morgenstern-Platz 1 2.Stock
Thursday 15.12. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Thursday 12.01. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Thursday 19.01. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Thursday 26.01. 09:45 - 13:00 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock

Information

Aims, contents and method of the course

Curriculum: Elective course of Bachelor in Economics, 2 SSt, 4 ECTS

Prerequisites: previously attended bachelor game theory class

At first sight "Theories" and "Bounded Rationality" seem to contradict one another.
And yet bounded rationality consists of everything that does not belong to the
category of being rational. The term rationality is reserved for the classic paradigm of
decision making in Economics where (it is as if) the decision maker has precise beliefs
about the likelihood that each possible event will occur and makes decisions by
maximizing expected utility. Thus, any deviation from this paradigm falls in the
category of bounded rationality. So bounded rationality encompasses optimization
under alternative criteria, heuristics, rules of thumb, ad-hoc behavior and even
mistakes.
In this lecture we will introduce and discuss the field of bounded rationality that lies
closest to rationality, namely where the decision maker chooses actions that are
optimal according to some specified criteria or "theories".
Theories are valuable as they identify the foundations of predictions and create
benchmarks for comparison to observed behavior.
Bounded rational theories are valuable when the assumptions underlying rational
decision making are less plausible and when one is not willing to characterize behavior
as ad-hoc just because it does not conform to the most stringent framework of rational
decision making.
Excitement rises when one is able to explain common behavioral patterns such as
imitation and reinforcement as optimal according to one of these theories. Theories
provide additional insights when one learns that particular forms "work" while others do not. For instance, a particular form of imitation can lead all to jointly learn what is
best. However, to simply imitate the more successful can lead to the opposite
outcome where everyone chooses the worst action in the long run.
Some of the results presented in the lecture have only been discovered very recently
which makes the topic interesting but makes reading cumbersone. Supplementary
reading will mostly original research articles, to be used to get a general idea, their
deeper understanding is beyond the scope of this lecture. All material will be
presented in the class in a very simple context.

Topics will be presented in the following order:
Making a choice for the first time: rational, maximin utility, minimax regret (French,
1986, Stoye, 2009)
Making the choice for tomorrow based on today: how to reinforce (Börgers et al,
2004), how to imitate (Schlag, 1998, Alos-Ferrer and Schlag, 2007)
Planning for the long run: the role of memory (Rustichini, 1999), evolution and
reinforcement (Börgers and Sarin, 1997), social learning and imitation (Schlag, 1998)

Assessment and permitted materials

45% midterm, 45% final (29.1.2015), 10% homeworks

Minimum requirements and assessment criteria

Examination topics

Reading list

Alos-Ferrer, C. and K.H. Schlag (2007), Imitation and Learning, Handbook of Rational
and Social Choice, Chapter 11, http://www.uni-konstanz.de/micro/team/alosferrer/
papers/Imitation.pdf.
Börgers, T, A.J. Morales, and R. Sarin (2004), Expedient and monotone learning rules,
Econometrica 72, 383-405.
Börgers, T. and R. Sarin (1997) Learning Through Reinforcement and Replicator
Dynamics, Journal of Economic Theory 77, 1-14.
French, S. (1986). Decision Theory. Halsted Press, NewYork.
Rustichini, A. (1999) Optimal Properties of Stimulus-Response Learning Models,
Games and Economic Behavior 29, 244-273.
Schlag, K.H. (1998) Why Imitate, and if so, How? A Boundedly Rational Approach to
Multi-Armed Bandits, Journal of Economic Theory 78(1), 130-156.
Schlag, K.H. Distribution-Free Learning, Working Paper ECO 2007/1, European
University Institute, 2006.
Stoye, J. (2011), Statistical Decisions under Ambiguity, "Statistical Decisions under
Ambiguity," Theory and Decision 70, 129-148.

Association in the course directory

Last modified: Mo 07.09.2020 15:29