Introducing Gamettes: A Playful Approach for Capturing Decision-Making for Informing Behavioral Models

2020 ◽  
Author(s):  
Omid Mohaddesi ◽  
Yifan Sun ◽  
Rana Azghandi ◽  
Rozhin Doroudi ◽  
Sam Snodgrass ◽  
...  
Keyword(s):  
Decision Making ◽  
Behavioral Models

Behavioral Models of Managerial Decision-Making

2011 ◽  
Author(s):  
Avi Goldfarb ◽  
Teck H. Ho ◽  
Wilfred Amaldoss ◽  
Alexander L. Brown ◽  
Yan Chen ◽  
...  
Keyword(s):  
Decision Making ◽  
Behavioral Models ◽  
Managerial Decision ◽  
Managerial Decision Making

scholarly journals On comparison of the principles of equivalent utility and its applications

2019 ◽  
Vol 11 (2) ◽  
pp. 240-249
Author(s):  
M. Chudziak
Keyword(s):  
Decision Making ◽  
Probability Space ◽  
Random Variable ◽  
Insurance Premium ◽  
Behavioral Models ◽  
Decision Making Under Risk ◽  
Rank Dependent Utility ◽  
Positive Homogeneity ◽  
Bounded Random Variable ◽  
Negative Real Number

An insurance premium principle is a way of assigning to every risk, represented by a non-negative bounded random variable on a given probability space, a non-negative real number. Such a number is interpreted as a premium for the insuring risk. In this paper the implicitly defined principle of equivalent utility is investigated. Using the properties of the quasideviation means, we characterize a comparison in the class of principles of equivalent utility under Rank-Dependent Utility, one of the important behavioral models of decision making under risk. Then we apply this result to establish characterizations of equality and positive homogeneity of the principle. Some further applications are discussed as well.

scholarly journals Decision from Experience Behavior Modeling (DEBM): an open-source Python package for developing, evaluating, and visualizing behavioral models.

2022 ◽  
Author(s):  
Ofir Yakobi ◽  
Yefim Roth
Keyword(s):  
Social Sciences ◽  
Decision Making ◽  
Parameter Estimation ◽  
Open Source ◽  
Research Field ◽  
Behavior Modeling ◽  
Grid Search ◽  
Behavioral Models ◽  
The Social ◽  
Python Package

The last decade was characterized by an emphasis on enhancing reproducibility and replicability in the social sciences. To contribute to these efforts within the decision-making research field, we introduce DEBM (Decision from Experience Behavior Modeling) – an open-source Python package. The main goal of DEBM is to serve as a central colloberative pool of models and methods in the decision from experience domain. Specifically, it provides a convenient “playground” for developing models or experimenting with existing ones. DEBM includes many features such as multiprocessing, parameter estimation, visualization, and more. In this paper we cover the basic functionality of DEBM by simulating behavior using an existing model and given parameters, and recovering these parameters using grid search.

Measuring Utility, Destabilizing EUT

2018 ◽  
pp. 261-280
Author(s):  
Ivan Moscati
Keyword(s):  
Decision Making ◽  
Behavioral Economics ◽  
Expected Utility ◽  
Utility Theory ◽  
Expected Utility Theory ◽  
Behavioral Models ◽  
Decision Making Under Risk ◽  
Utility Measurement ◽  
Elicitation Methods ◽  
Series Of Experiments

Chapter 16 shows how the validity of expected utility theory (EUT) was increasingly called into question between the mid-1960s and the mid-1970s and discusses how a series of experiments performed from 1974 to 1985 undermined the earlier confidence that EUT makes it possible to measure utility. Beginning in the mid-1960s, in a series of experiments seminal to the field later called behavioral economics, Sarah Lichtenstein, Paul Slovic, Amos Tversky, and others showed that decision patterns violating EUT are systematic. The new experimenters who engaged with the EUT-based measurement of utility from the mid-1970s, namely Uday Karmarkar, Richard de Neufville, Paul Schoemaker, and coauthors, showed that different elicitation methods to measure utility, which according to EUT should produce the same outcome, generate different measures. These findings contributed to destabilizing EUT, undermined the confidence in EUT-based utility measurement, and helped foster a blossoming of novel behavioral models of decision-making under risk.

scholarly journals Neural Correlates of Sequence Learning with Stochastic Feedback

2011 ◽  
Vol 23 (6) ◽  
pp. 1346-1357
Author(s):  
Bruno B. Averbeck ◽  
James Kilner ◽  
Christopher D. Frith
Keyword(s):  
Decision Making ◽  
Sequence Learning ◽  
Premotor Cortex ◽  
Learning Task ◽  
Neural Correlates ◽  
Single Step ◽  
Button Press ◽  
Behavioral Models ◽  
Sequential Decision ◽  
Early Effect

Although much is known about decision making under uncertainty when only a single step is required in the decision process, less is known about sequential decision making. We carried out a stochastic sequence learning task in which subjects had to use noisy feedback to learn sequences of button presses. We compared flat and hierarchical behavioral models and found that although both models predicted the choices of the group of subjects equally well, only the hierarchical model correlated significantly with learning-related changes in the magneto-encephalographic response. The significant modulations in the magneto-encephalographic signal occurred 83 msec before button press and 67 msec after button press. We also localized the sources of these effects and found that the early effect localized to the insula, whereas the late effect localized to the premotor cortex.

scholarly journals Stress increases impulsive punishment avoidance in unmedicated mood disorders

2021 ◽  
Author(s):  
Kristoffer Aberg
Keyword(s):  
Decision Making ◽  
Avoidance Response ◽  
Mood Disorders ◽  
Avoidance Behavior ◽  
Induce Stress ◽  
Behavioral Models ◽  
Behavioral Biases ◽  
Learning Rates ◽  
Original Dataset ◽  
Electric Shocks

In an intriguing study designed to test whether and how stress affects learning and decision making in anxious individuals, Aylward et al. (2019)1 used a restless four-armed bandit task, where threat of electric shocks was used to induce stress. They hypothesized that anxious individuals would learn faster from punishments under stress, and as a result, exhibit choices that are more affected by those punishments. Unfortunately, these hypotheses were not confirmed.Here, we re-analyzed the original dataset using behavioral models that incorporate different mechanisms that could account for punishment-related behavioral biases. We found evidence that support the original hypotheses, namely increased punishment-avoidance for anxious individuals during stress. The avoidance-behavior was driven by punishments that were presented following a sequence of neutral outcomes, and in turn increased the tendency to elicit an immediate avoidance response (rather than larger learning rates). This impulsive avoidance bias was particularly pronounced in anxious individuals during stress.

scholarly journals Development of macroeconomic models based on behavioral economics: issues and further research

2021 ◽  
pp. 2-2
Author(s):  
М. Talavyrya ◽  
◽  
B. Dorosh ◽  
Keyword(s):  
Decision Making ◽  
Behavioral Economics ◽  
Basic Concept ◽  
Behavioral Models ◽  
Practical Application ◽  
Macroeconomic Models ◽  
The Past ◽  
Behavioral Macroeconomics ◽  
Key Issues ◽  
Central Bankers

The article analyzes the formation, spread and development of behavioral economics in microeconomic research, as well as its development in macroeconomic research over the past two decades. The key shortcomings of neoclassical macroeconomic models and their critique based on existing research and practical application by central bankers are highlighted. The key stages in the formation of behavioral macroeconomics, elements of which began to appear in the works of neoclassical macroeconomists, have been identified. The main arguments in favor of replacing neoclassical macroeconomic models with new behavioral macroeconomic models are presented, as well as key issues of behavioral macroeconomics and prospects for its further adoption as a basic concept for decision-making for governments. Key studies of behavioral economists on behavioral macroeconomic models, most of which are agents-based (microfoundations-based), have been identified and systematized. Based on the results of testing various behavioral models by world-renowned scientists, as well as our analysis, it is proposed to focus further macroeconomic research on behavioral models based on the activities of agents (microfoundations).

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