In a companion paper [1], we have presented a generic approach for inferring how subjects make optimal decisions under uncertainty. From a Bayesian decision theoretic perspective, uncertain representations correspond to “posterior” beliefs, which result from integrating (sensory) information with subjective “prior” beliefs. Preferences and goals are encoded through a “loss” (or “utility”) function, which measures the cost incurred by making any admissible decision for any given (hidden or unknown) state of the world. By assuming that subjects make optimal decisions on the basis of updated (posterior) beliefs and utility (loss) functions, one can evaluate the likelihood of observed behaviour. In this paper, we describe a concrete implementation of this meta-Bayesian approach (i.e. a Bayesian treatment of Bayesian decision theoretic predictions) and demonstrate its utility by applying it to both simulated and empirical reaction time data from an associative learning task. Here, inter-trial variability in reaction times is modelled as reflecting the dynamics of the subjects' internal recognition process, i.e. the updating of representations (posterior densities) of hidden states over trials while subjects learn probabilistic audio-visual associations. We use this paradigm to demonstrate that our meta-Bayesian framework allows for (i) probabilistic inference on the dynamics of the subject's representation of environmental states, and for (ii) model selection to disambiguate between alternative preferences (loss functions) human subjects could employ when dealing with trade-offs, such as between speed and accuracy. Finally, we illustrate how our approach can be used to quantify subjective beliefs and preferences that underlie inter-individual differences in behaviour.
In this paper, we present a generic approach that can be used to infer how subjects make optimal decisions under uncertainty. This approach induces a distinction between a subject’s perceptual model, which underlies the representation of a hidden "state of affairs" and a response model, which predicts the ensuing behavioural (or neurophysiological) responses to those inputs. We start with the premise that subjects continuously update a probabilistic representation of the causes of their sensory inputs to optimise their behaviour. In addition, subjects have preferences or goals that guide decisions about actions given the above uncertain representation of these hidden causes or state of affairs. From a Bayesian decision theoretic perspective, uncertain representations are so-called "posterior" beliefs, which are influenced by subjective "prior" beliefs. Preferences and goals are encoded through a "loss" (or "utility") function, which measures the cost incurred by making any admissible decision for any given (hidden) state of affair. By assuming that subjects make optimal decisions on the basis of updated (posterior) beliefs and utility (loss) functions, one can evaluate the likelihood of observed behaviour. Critically, this enables one to "observe the observer", i.e. identify (context- or subject-dependent) prior beliefs and utility-functions using psychophysical or neurophysiological measures. In this paper, we describe the main theoretical components of this meta-Bayesian approach (i.e. a Bayesian treatment of Bayesian decision theoretic predictions). In a companion paper (‘Observing the observer (II): deciding when to decide’), we describe a concrete implementation of it and demonstrate its utility by applying it to simulated and real reaction time data from an associative learning task.
The integration of economics and psychology has created a vibrant and fruitful emerging field of study. The essays in Economics and Psychology take a broad view of the interface between these two disciplines, going beyond the usual focus on "behavioral economics." As documented in this volume, the influence of psychology on economics has been responsible for a view of human behavior that calls into question the assumption of complete rationality (and raises the possibility of altruistic acts), the acceptance of experiments as a valid method of economic research, and the idea that utility or well-being can be measured.
The contributors, all leading researchers in the field, offer state-of-the-art discussions of such topics as pro-social behavior and the role of conditional cooperation and trust, happiness research as an empirical tool, the potential of neuroeconomics as a way to deepen understanding of individual decision making, and procedural utility as a concept that captures the well-being people derive directly from the processes and conditions leading to outcomes. Taken together, the essays in Economics and Psychology offer an assessment of where this new interdisciplinary field stands and what directions are most promising for future research, providing a useful guide for economists, psychologists, and social scientists.
The USI Career Service is glad to invite you to the seminar organized by the Master in Financial Communication, Master in Banking and Finance and Master in Finance: Private equity and corporate advice in Wealth management within the Seminar on Private Banking April 24, 2017, 3.30pm Room ...
The USI Career Service is glad to invite you to the seminar organized by the Master in Financial Communication, Master in Banking and Finance and Master in Finance: Family Business and family governance for UHNWI within the Seminar on Private Banking April 10, 2017, 3.30pm Room A-23, USI, ...
The USI Career Service is glad to invite you to the seminar organized by the Master in Financial Communication, Master in Banking and Finance and Master in Finance: Main regulatory actions affecting the wealth management industry within the Seminar on Private Banking April 3, 2017, 3.30pm ...
Speaker: Dan Alistarh IST, Austria Date: Tuesday, April 4, 2017 Place: USI Lugano Campus, room SI-003, informatics building (Via G. Buffi 13) Time: 15:30 ...
Speaker: Andreas Galanis University of Oxford, UK Date: Wednesday, March 29, 2017 Place: USI Lugano Campus, room A34, Red building (Via G. Buffi 13) Time: 09:30 Abstract: Graphical models are a broad framework from statistics with ...
Speaker: Gerhard Wellein University of Erlangen-Nuremberg, Germany Date: Wednesday, March 29, 2017 Place: USI Lugano Campus, room SI-006, informatics building (Via G. Buffi 13) Time: 13:30 ...
