Course Structure

This course has three components. Lectures present new material and exercises allow the participants to master this material. The first two days are devoted to lectures and exercises. The last two days are devoted to mini-projects which are formulated and implemented by the participants, in small groups. This facilitates the thorough internalization of the concepts and methods learned, their integration with other methods familiar to the participants, and their application to problems of interest.

Daily Schedule

Monday - Wednesday: 09:00 - 12:00, 13:00 - 16:00, room CM107
Thursday: 09:00 - 12:00, room CM221

Detailed schedule

Lecture Topics

In the lectures we will consider the following topics.

The art of uncertainty modelling. Quantitative models and data, as well as conceptual understanding, are important in formulating decisions. Often the uncertainties surrounding these entities are subtle and require careful modelling in themselves. Info-gap models of uncertainty are useful for representing severe uncertainty. Combination of info-gap and probabilistic models is discussed.

Preference reversal under competition. Numerous paradoxes of decision under uncertainty--Ellsberg, Allais, and others--entail reversal of preferences between options. We explain how info-gap robust-satisficing provides an explanation.

Relation between robust-satisficing and min-max. These strategies are interchangeable as tools for describing observed behavior of an agent. However, they can lead to very different choices when used by an agent to select an action, depending on the agent's beliefs. We explain the observational equivalence and behavioral difference between these decision strategies.

Robustness and the probability of survival. Evidence suggests that agents in uncertain competition do not always try to optimize, but rather try to satisfice their outcomes. We discuss conditions for sub-optimal robust-satisficing being equivalent to maximizing the probability of survival.

Opportuneness: The other side of uncertainty. Uncertainty can be either pernicious (threatening failure), or propitious (offering windfall). We discuss the relation between info-gap robust-satisficing and opportune-windfalling, and show how these strategies can be combined in decision making.