scholarly journals Modeling Statistical Insensitivity: Sources of Suboptimal Behavior

2016 ◽  
Vol 41 (1) ◽  
pp. 188-217 ◽  
Author(s):  
Annie Gagliardi ◽  
Naomi H. Feldman ◽  
Jeffrey Lidz
Keyword(s):  
Suboptimal Behavior

scholarly journals Valuation of knowledge and ignorance in mesolimbic reward circuitry

2018 ◽  
Vol 115 (31) ◽  
pp. E7255-E7264 ◽  
Author(s):  
Caroline J. Charpentier ◽  
Ethan S. Bromberg-Martin ◽  
Tali Sharot
Keyword(s):  
Human Brain ◽  
Orbitofrontal Cortex ◽  
Information Seeking ◽  
Neural Coding ◽  
Basic Feature ◽  
Neural Computation ◽  
Reward Circuitry ◽  
General Preference ◽  
To Receive ◽  
Suboptimal Behavior

The pursuit of knowledge is a basic feature of human nature. However, in domains ranging from health to finance people sometimes choose to remain ignorant. Here, we show that valence is central to the process by which the human brain evaluates the opportunity to gain information, explaining why knowledge may not always be preferred. We reveal that the mesolimbic reward circuitry selectively treats the opportunity to gain knowledge about future favorable outcomes, but not unfavorable outcomes, as if it has positive utility. This neural coding predicts participants’ tendency to choose knowledge about future desirable outcomes more often than undesirable ones, and to choose ignorance about future undesirable outcomes more often than desirable ones. Strikingly, participants are willing to pay both for knowledge and ignorance as a function of the expected valence of knowledge. The orbitofrontal cortex (OFC), however, responds to the opportunity to receive knowledge over ignorance regardless of the valence of the information. Connectivity between the OFC and mesolimbic circuitry could contribute to a general preference for knowledge that is also modulated by valence. Our findings characterize the importance of valence in information seeking and its underlying neural computation. This mechanism could lead to suboptimal behavior, such as when people reject medical screenings or monitor investments more during bull than bear markets.

Kludged

2011 ◽  
Vol 3 (3) ◽  
pp. 210-231 ◽  
Author(s):  
Jeffrey C Ely
Keyword(s):  
Marginal Adaptation ◽  
Internal Process ◽  
Adaptive Processes ◽  
To Come ◽  
Suboptimal Behavior ◽  
Fundamental Design

Is there reason to believe that our brains have evolved to make efficient decisions so that the details of the internal process are irrelevant? I develop a model which illustrates a limitation of adaptive processes: improvements tend to come in the form of kludges. A kludge is a marginal adaptation that compensates for, but does not eliminate, fundamental design inefficiencies. When kludges accumulate, the result can be perpetually suboptimal behavior even in a model of evolution in which arbitrarily large innovations occur infinitely, often with probability 1. (JEL D03, D87)

IMPROVING SVM PERFORMANCE IN MULTI-LABEL DOMAINS: THRESHOLD ADJUSTMENT

2013 ◽  
Vol 22 (01) ◽  
pp. 1250038 ◽  
Author(s):  
PEERAPON VATEEKUL ◽  
SAREEWAN DENDAMRONGVIT ◽  
MIROSLAV KUBAT
Keyword(s):  
Classification Performance ◽  
Support Vector ◽  
Binary Classifier ◽  
Research Groups ◽  
Computational Costs ◽  
Vector Machines ◽  
Threshold Adjustment ◽  
Good Classification ◽  
Good Classification Performance ◽  
Suboptimal Behavior

In “multi-label domains,” where the same example can simultaneously belong to two or more classes, it is customary to induce a separate binary classifier for each class, and then use them all in parallel. As a result, some of these classifiers are induced from imbalanced training sets where one class outnumbers the other – a circumstance known to hurt some machine learning paradigms. In the case of Support Vector Machines (SVM), this suboptimal behavior is explained by the fact that SVM seeks to minimize error rate, a criterion that is in domains of this type misleading. This is why several research groups have studied mechanisms to readjust the bias of SVM's hyperplane. The best of these achieves very good classification performance at the price of impractically high computational costs. We propose here an improvement where these cost are reduced to a small fraction without significantly impairing classification.

scholarly journals The Value of Research in Comparative Cognition

2018 ◽  
Vol 31 ◽  
Author(s):  
Thomas R. Zentall
Keyword(s):  
Conditioned Reinforcement ◽  
Comparative Research ◽  
Comparative Cognition ◽  
Comparative Psychology ◽  
Positive Contrast ◽  
Comparative Approach ◽  
Social Reinforcement ◽  
General Terms ◽  
Control Of Variables ◽  
Suboptimal Behavior

Most research of comparative cognition has focused on the degree to which cognitive phenomena that have been reported in humans, especially children, can also be demonstrated in other animals. The value of such comparative research has not only been the finding that other animals show behavior that is qualitatively similar to that of humans but because the comparative approach calls for the careful control of variables often confounded with the mechanisms being tested, the comparative approach has identified procedures that could also improve the design of research with humans. The comparative approach has also been used to study the degree to which other animals demonstrate human biases and suboptimal behavior (e.g., commercial gambling). When applied to this field of research, the comparative approach has generally taken the position that human biases generally thought to be established by complex social and societal mechanisms (e.g., social reinforcement and entertainment) may be more parsimoniously accounted for by simpler mechanisms (i.e., conditioned reinforcement and positive contrast). When explained in terms of these mechanisms, the results have implications for explaining in simpler and more general terms the results of similar research with humans. Thus, comparative psychology tells us not only about the similarities and possible differences in behavior among species but it also may have implications for our understanding of similar behavior in humans.

scholarly journals Cognitive Abilities and Household Financial Decision Making

2013 ◽  
Vol 5 (1) ◽  
pp. 193-207 ◽  
Author(s):  
Sumit Agarwal ◽  
Bhashkar Mazumder
Keyword(s):  
Decision Making ◽  
Cognitive Abilities ◽  
Test Scores ◽  
Credit Cards ◽  
Home Equity ◽  
Financial Decisions ◽  
Financial Decision Making ◽  
Math Scores ◽  
Financial Decision ◽  
Suboptimal Behavior

We analyze the effects of cognitive abilities on two examples of consumer financial decisions where suboptimal behavior is well defined. The first example features the optimal use of credit cards for convenience transactions after a balance transfer and the second involves a financial mistake on a home equity loan application. We find that consumers with higher overall test scores, and specifically those with higher math scores, are substantially less likely to make a financial mistake. These mistakes are generally not associated with nonmath test scores. (JEL D14, G21)

scholarly journals Suboptimal behavior of Bayes and MDL in classification under misspecification

2007 ◽  
Vol 66 (2-3) ◽  
pp. 119-149 ◽  
Author(s):  
Peter Grünwald ◽  
John Langford
Keyword(s):  
Suboptimal Behavior
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