scholarly journals Experience and rationality under risk: re-examining the impact of sampling experience

2020 ◽  
Vol 23 (4) ◽  
pp. 1100-1128
Author(s):  
Ilke Aydogan ◽  
Yu Gao
Keyword(s):  
Decision Making ◽  
Expected Utility ◽  
Decision Models ◽  
Decision Making Under Uncertainty ◽  
Probability Weighting ◽  
Sampling Without Replacement ◽  
Decisions Under Risk ◽  
Lack Of Control ◽  
The Impact ◽  
Small Probabilities

Abstract A recent strand of the literature on decision-making under uncertainty has pointed to an intriguing behavioral gap between decisions made from description and decisions made from experience. This study reinvestigates this description-experience gap to understand the impact that sampling experience has on decisions under risk. Our study adopts a complete sampling paradigm to address the lack of control over experienced probabilities by requiring complete sampling without replacement. We also address the roles of utilities and ambiguity, which are central in most current decision models in economics. Thus, our experiment identifies the deviations from expected utility due to over- (or under-) weighting of probabilities. Our results confirm the existence of the behavioral gap, but they provide no evidence for the underweighting of small probabilities within the complete sampling treatment. We find that sampling experience attenuates rather than reverses the inverse S-shaped probability weighting under risk.

scholarly journals Evaluating the impact of visualization of wildfire hazard upon decision-making under uncertainty

2016 ◽  
Vol 30 (7) ◽  
pp. 1377-1404 ◽  
Author(s):  
Lisa Cheong ◽  
Susanne Bleisch ◽  
Allison Kealy ◽  
Kevin Tolhurst ◽  
Tom Wilkening ◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Making Under Uncertainty ◽  
Wildfire Hazard ◽  
The Impact

On the impact of experience on probability weighting in decisions under risk.

Decision ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. 153-162 ◽  
Author(s):  
Doron Cohen ◽  
Ori Plonsky ◽  
Ido Erev
Keyword(s):  
Probability Weighting ◽  
Decisions Under Risk ◽  
The Impact

Examining the Impact of Training and Feedback on Visualization-Supported Decision Making under Uncertainty

2018 ◽  
Vol 62 (1) ◽  
pp. 1449-1453
Author(s):  
Jihye Song ◽  
Olivia B. Newton ◽  
Stephen M. Fiore ◽  
Jonathan Coad ◽  
Jared Clark ◽  
...  
Keyword(s):  
Decision Making ◽  
Ecological Validity ◽  
Critical Role ◽  
Decision Making Under Uncertainty ◽  
Cognitive Efficiency ◽  
Training Interventions ◽  
Complex Decision Making ◽  
Complex Decision ◽  
Task Training ◽  
The Impact

Empirical evaluations of uncertainty visualizations often employ complex experimental tasks to ensure ecological validity. However, if training for such tasks is not sufficient for naïve participants, differences in performance could be due to the visualizations or to differences in task comprehension, making interpretation of findings problematic. Research has begun to assess how training is related to performance on decision-making tasks using uncertainty visualizations. This study continues this line of research by investigating how training, in general, and feedback, in particular, affect performance on a simulated resource allocation task. Additionally, we examined how this alters metacognition and workload to produce differences in cognitive efficiency. Our results suggest that, on a complex decision-making task, training plays a critical role in performance with respect to accuracy, subjective workload, and cognitive efficiency. This study has implications for improving research on complex decision making, and for designing more efficacious training interventions to assess uncertainty visualizations.

scholarly journals Adaptive Modeling for Risk-Aware Decision Making

2019 ◽  
Vol 33 ◽  
pp. 9896-9897
Author(s):  
Sandhya Saisubramanian
Keyword(s):  
Decision Making ◽  
Autonomous Agent ◽  
Decision Making Under Uncertainty ◽  
Risk Awareness ◽  
Reasoning Under Uncertainty ◽  
Adaptive Modeling ◽  
Trade Off ◽  
Core Capability ◽  
The Impact

This thesis aims to provide a foundation for risk-aware decision making. Decision making under uncertainty is a core capability of an autonomous agent. A cornerstone for with long-term autonomy and safety is risk-aware decision making. A risk-aware model fully accounts for a known set of risks in the environment, with respect to the problem under consideration, and the process of decision making using such a model is risk-aware decision making. Formulating risk-aware models is critical for robust reasoning under uncertainty, since the impact of using less accurate models may be catastrophic in extreme cases due to overly optimistic view of problems. I propose adaptive modeling, a framework that helps balance the trade-off between model simplicity and risk awareness, for different notions of risks, while remaining computationally tractable.

Probability Dominance

2020 ◽  
Vol 102 (5) ◽  
pp. 1006-1020
Author(s):  
Enrico Diecidue ◽  
Haim Levy ◽  
Moshe Levy
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Expected Utility ◽  
Cumulative Prospect Theory ◽  
Economic Consequences ◽  
Regret Theory ◽  
Decisions Under Risk ◽  
Set Up ◽  
Winner Take All ◽  
Probability Dominance

The most commonly employed paradigms for decision making under risk are expected utility, prospect theory, and regret theory. We examine the simple heuristic of maximizing the probability of being ahead, which in some natural economic situations may be in contradiction to all three of the above fundamental paradigms. We test whether this heuristic, which we call probability dominance (PD), affects decisions under risk. We set up head-to-head situations where all preferences of a given class (expected utility, original or cumulative prospect theory, or regret theory) favor one alternative yet PD favors the other. Our experiments reveal that 49% of subjects' choices are aligned with PD in contradiction to any form of expected utility or prospect theory maximization; 73% are aligned with PD as opposed to preferences under risk aversion and under original and cumulative prospect theory preferences; and 68% to 76% are aligned with PD contradicting preferences under regret theory. We conclude that probability dominance substantially affects choices and should therefore be incorporated into decision-making models. We show that PD has significant economic consequences. The PD heuristic may have evolved through situations of winner-take-all competition.

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