scholarly journals Conformist social learning inoculates against adverse risk aversion

2021 ◽  
Author(s):  
Wataru Toyokawa ◽  
Wolfgang Gaissmaier
Keyword(s):  
Decision Making ◽  
Social Learning ◽  
Risk Aversion ◽  
Negative Feedback ◽  
Risk Taking ◽  
Human Subjects ◽  
Informational Cascades ◽  
Minority Influence ◽  
Positive And Negative Feedback ◽  
Error Learning

AbstractGiven the ubiquity of potentially adverse biases incurred by trial-and-error learning, it seems paradoxical that improvements in decision-making performance through conformist social learning, a process widely considered to be bias amplification, still prevail in animal behaviour. Here we show, through model analyses and online experiments with 467 adult human subjects, that conformity can promote favourable risk taking in repeated decision making, even though many individuals are systematically biased towards suboptimal risk aversion owing to the myopia of reinforcement learning. Although positive feedback conferred by conformity could result in suboptimal informational cascades, our dynamic model of behaviour identified a key role for negative feedback that arises when a weak minority influence undermines the inherent behavioural bias. This ‘collective behavioural rescue’, emerging through coordination of positive and negative feedback, highlights a benefit of social learning in a broader range of environmental conditions than previously assumed and resolves the ostensible paradox of adaptive collective flexibility through conformity.

scholarly journals Revisiting pest sampling plans in light of economic uncertainty and risk aversion.

2020 ◽  
Author(s):  
Diego F. Rincon ◽  
Hugo Fernando Rivera-Trujillo ◽  
Lorena Mojica-Ramos ◽  
Felipe Borrero-Echeverry
Keyword(s):  
Decision Making ◽  
Risk Aversion ◽  
Computer Simulations ◽  
Binary Data ◽  
Human Subjects ◽  
Decision Threshold ◽  
Market Uncertainty ◽  
Economic Threshold ◽  
Tomato Crop ◽  
Sampling Plans

Abstract Decision-making for pest management in agriculture is often assisted by sampling plans that guide users in determining the need for an intervention. Even though Tuta absoluta is easily recognizable by most tomato growers and that several sampling plans have been developed, adoption of decision-making systems for this pest is still incipient. Two potential obstacles for adoption are market uncertainty and farmer's risk aversion. Both obstacles could be tackled by adopting sampling plans that allow farmers to plan interventions according to rough estimations of economic thresholds and the intuition and experience gained by farmers. In this study, we evaluated four sampling plans using computer simulations and field trials. We compared the efficiency and the ability of each plan to both estimate the actual mean number of larvae per plant and to classify pest populations according to a predefined economic threshold. We also analyzed the time spent, and plants examined by human subjects applying each plan on a tomato crop with a T. absoluta infestation slightly over a predefined economic threshold. We show that sampling plans that deliver the most precise classifications, are poorest in delivering pest density estimations and vice versa. Our findings are consistent for both human subjects and computer simulations. However, the average number of samples required by sampling plans does not reflect the time spent by humans sampling real plants. Our results show that sampling plans based on counts, as opposed to those based on binary data, can efficiently provide reliable information on a current level of T. absoluta infestation relative to an estimated decision threshold. We suggest that sampling plans that promote the creation of farmer's memory, such as those based on counts, may be more suitable to both reduce risk aversion and increase adaptability to market uncertainty.

Blunted feedback processing during risky decision making in adolescents with a parental history of substance use disorders

2013 ◽  
Vol 25 (4pt1) ◽  
pp. 1119-1136 ◽  
Author(s):  
Anja S. Euser ◽  
Kirstin Greaves-Lord ◽  
Michael J. Crowley ◽  
Brittany E. Evans ◽  
Anja C. Huizink ◽  
...  
Keyword(s):  
Decision Making ◽  
Substance Use ◽  
Substance Use Disorders ◽  
Negative Feedback ◽  
Risky Decision Making ◽  
Risky Decision ◽  
Parental History ◽  
Feedback Processing ◽  
History Of ◽  
Positive And Negative Feedback

AbstractRisky decision making, a hallmark phenotype of substance use disorders (SUD), is thought to be associated with deficient feedback processing. Whether these aberrations are present prior to SUD onset or reflect merely a consequence of chronic substance use on the brain remains unclear. The present study investigated whether blunted feedback processing during risky decision making reflects a biological predisposition to SUD. We assessed event-related potentials elicited by positive and negative feedback during performance of a modified version of the Balloon Analogue Risk Task (BART) among high-risk adolescents with a parental history of SUD (HR; n = 61) and normal-risk controls (NR; n = 91). HR males made significantly more risky and faster decisions during the BART than did NR controls. Moreover, HR adolescents showed significantly reduced P300 amplitudes in response to both positive and negative feedback as compared to NR controls. These differences were not secondary to prolonged substance use exposure. Results are discussed in terms of feedback-specific processes. Reduced P300 amplitudes in the BART may reflect poor processing of feedback at the level of overall salience, which may keep people from effectively predicting the probability of future gains and losses. Though conclusions are tentative, blunted feedback processing during risky decision making may represent a promising endophenotypic vulnerability marker for SUD.

scholarly journals Feedback-related Brain Potential Activity Complies with Basic Assumptions of Associative Learning Theory

2012 ◽  
Vol 24 (4) ◽  
pp. 794-808 ◽  
Author(s):  
David Luque ◽  
Francisco J. López ◽  
Josep Marco-Pallares ◽  
Estela Càmara ◽  
Antoni Rodríguez-Fornells
Keyword(s):  
Associative Learning ◽  
Negative Feedback ◽  
Error Term ◽  
Human Subjects ◽  
Learning Task ◽  
Learning Models ◽  
Feedback Processing ◽  
Predictive Learning ◽  
Positive And Negative Feedback ◽  
Potential Activity

Feedback-related negativity (FRN) is an ERP component that distinguishes positive from negative feedback. FRN has been hypothesized to be the product of an error signal that may be used to adjust future behavior. In addition, associative learning models assume that the trial-to-trial learning of cue–outcome mappings involves the minimization of an error term. This study evaluated whether FRN is a possible electrophysiological correlate of this error term in a predictive learning task where human subjects were asked to learn different cue–outcome relationships. Specifically, we evaluated the sensitivity of the FRN to the course of learning when different stimuli interact or compete to become a predictor of certain outcomes. Importantly, some of these cues were blocked by more informative or predictive cues (i.e., the blocking effect). Interestingly, the present results show that both learning and blocking affect the amplitude of the FRN component. Furthermore, independent analyses of positive and negative feedback event-related signals showed that the learning effect was restricted to the ERP component elicited by positive feedback. The blocking test showed differences in the FRN magnitude between a predictive and a blocked cue. Overall, the present results show that ERPs that are related to feedback processing correspond to the main predictions of associative learning models.

scholarly journals The Effect of Positive and Negative Feedback on Risk-Taking across Different Contexts

PLoS ONE ◽  
2015 ◽  
Vol 10 (9) ◽  
pp. e0139010 ◽  
Author(s):  
Annabel B. Losecaat Vermeer ◽  
Alan G. Sanfey
Keyword(s):  
Negative Feedback ◽  
Risk Taking ◽  
Positive And Negative Feedback

Motivating Innovation: The Effect of Loss Aversion on the Willingness to Persist

2020 ◽  
Vol 102 (3) ◽  
pp. 569-582 ◽  
Author(s):  
Yaroslav Rosokha ◽  
Kenneth Younge
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Incremental Cost ◽  
Prospect Theory ◽  
Negative Feedback ◽  
Loss Aversion ◽  
Model Uncertainty ◽  
Human Subjects ◽  
Two Dimensional ◽  
Randomized Experiments

We investigate the willingness of individuals to persist at exploration when confronted by prolonged periods of negative feedback. We design a two-dimensional maze game and run a series of randomized experiments with human subjects in the game. Our results suggest individuals explore more when they are reminded of the incremental cost of their actions, a result that extends prior research on loss aversion and prospect theory to environments characterized by model uncertainty. In addition, we run simulations based on a model of reinforcement learning that extend beyond two-period models of decision making to account for repeated behavior in longer-running, dynamic contexts.

scholarly journals Gambling on an empty stomach: Hunger modulates preferences for learned but not described risks

2021 ◽  
Author(s):  
Maaike M.H. van Swieten ◽  
Rafal Bogacz ◽  
Sanjay G. Manohar
Keyword(s):  
Decision Making ◽  
Risk Aversion ◽  
Risk Taking ◽  
Risk Preferences ◽  
The Other ◽  
Empty Stomach ◽  
Metabolic State ◽  
Strongly Coupled ◽  
Risk Seeking ◽  
Other Hand

AbstractWe assess risks differently when they are explicitly described, compared to when we learn directly from experience, suggesting dissociable decision-making systems. Our needs, such as hunger, could globally affect our risk preferences, but do they affect described and learned risks equally? On one hand, explicit decision-making is often considered flexible and contextsensitive, and might therefore be modulated by metabolic needs. On the other hand, implicit preferences learned through reinforcement might be more strongly coupled to biological drives. To answer this, we asked participants to choose between two options with different risks, where the probabilities of monetary outcomes were either described or learned. In agreement with previous studies, rewarding contexts induced risk-aversion when risks were explicitly described, but risk-seeking when they were learned through experience. Crucially, hunger attenuated these contextual biases, but only for learned risks. The results suggest that our metabolic state determines risk-taking biases when we lack explicit descriptions.

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