IMPERFECT DECISION MAKERS: ADMITTING

REAL-WORLD RATIONALITY

a workshop in conjunction with

the 30th Annual Conference on Neural Information Processing Systems (NIPS 2016)

 December 9, 2016, Barcelona, Spain

Centre de Convencions Internacional de Barcelona  

Location: Room 127+128 

WORKSHOP SCHEDULE 

The prescriptive Bayesian theory of decision making (DM) under uncertainty has reached a high level of maturity. The assumption that the decision maker is rational (i.e. that they optimize expected utility, in Savage's formulation) is central to this theory. However, empirical research indicates that this central assumption is often violated by real decision makers. This limits the ability of the prescriptive Bayesian theory to provide a descriptive theory of the real world. One of the reasons that have been proposed for why the assumption of rationality might be violated by real decision makers is the limited cognitive and computational resources of those decision makers. This workshop intends to inspect this core assumption and to consider possible ways to modify or complement it.
Many of the precise issues related to this theme can be formulated as questions:

• Does the concept of rationality require Bayesian reasoning?

• Does quantum probability theory (extending classical Kolmogorov probability) provide novel insights into the relation between decision making and cognition?

• Do the extensions of expected utility (which is a linear function of the relevant probabilities) to nonlinear functions of probabilities enhance the flexibility of a DM task formulating while respecting the limited cognitive resources of decision makers?

• How can good (meta-)heuristics, so successfully used by real-world decision makers, be elicited?

We expect that contributed talks, posters and informal discussions will extend this incomplete list. To stimulate discussions, the invited talks will be complemented by discussants challenging them. Altogether, the workshop aims to bring together diverse scientific communities, to brainstorm possible research directions, and to encourage collaboration among researchers with complementary ideas and expertise. The intended outcome is to understand and diminish the discrepancy between the established prescriptive theory and real-world DM.

 The targeted audience is the scientists and students from diverse communities (decision sciences, cognitive sciences, natural sciences, social science, engineering, etc.) interested in various aspects of rationality.

All accepted submissions will be published in the Workshop and Conference Proceedings series of the Journal of Machine Learning Research (JMRL).