N-Length and Number of Different N-Lengths as Determinants of Resistance to Extinction in Human Choice Behavior

1973 ◽  
Vol 23 (2) ◽  
pp. 255-259
Author(s):  
Stephen F. Davis
Keyword(s):  
Choice Behavior ◽  
Resistance To Extinction ◽  
Human Choice

Choice behavior and resistance to extinction

1962 ◽  
Vol 12 (1) ◽  
pp. 105-108 ◽  
Author(s):  
Allan R. Wagner ◽  
Norman Miller
Keyword(s):  
Choice Behavior ◽  
Resistance To Extinction

scholarly journals An Analysis of Decision Under Risk in Rats

2018 ◽  
Author(s):  
Christine M. Constantinople ◽  
Alex T. Piet ◽  
Carlos D. Brody
Keyword(s):  
Choice Behavior ◽  
Neural Substrates ◽  
Neural Mechanisms ◽  
Reference Dependence ◽  
Decision Making Under Risk ◽  
Internal Reference ◽  
Decision Under Risk ◽  
Psychological Phenomena ◽  
Human Choice ◽  
Behavioral Economic Theory

AbstractProspect Theory is the predominant behavioral economic theory describing decision-making under risk. It accounts for near universal aspects of human choice behavior whose prevalence may reflect fundamental neural mechanisms. We now apply Prospect Theory’s framework to rodents, using a task in which rats chose between guaranteed and probabilistic rewards. Like humans, rats distorted probabilities and showed diminishing marginal sensitivity, in which they were less sensitive to differences in larger rewards. They exhibited reference dependence, in which the valence of outcomes (gain or loss) was determined by an internal reference point reflecting reward history. The similarities between rats and humans suggest conserved neural substrates, and enable application of powerful molecular/circuit tools to study mechanisms of psychological phenomena from behavioral economics.

scholarly journals Imprecise Oracles Impose Limits to Predictability in Supervised Learning (Extended Abstract)

2021 ◽  
Author(s):  
Anjali Sifar ◽  
Nisheeth Srivastava
Keyword(s):  
Supervised Learning ◽  
Choice Behavior ◽  
State Of The Art ◽  
Ground Truth ◽  
Choice Models ◽  
Intrinsic Variability ◽  
Human Choice ◽  
Data Record ◽  
High Degree ◽  
Better Than

Supervised learning operates on the premise that labels unambiguously represent ground truth. This premise is reasonable in domains wherein a high degree of consensus is easily possible for any given data record, e.g. in agreeing on whether an image contains an elephant or not. However, there are several domains wherein people disagree with each other on the appropriate label to assign to a record, e.g. whether a tweet is toxic. We argue that data labeling must be understood as a process with some degree of domain-dependent noise and that any claims of predictive prowess must be sensitive to the degree of this noise. We present a method for quantifying labeling noise in a particular domain wherein people are seen to disagree with their own past selves on the appropriate label to assign to a record: choices under prospect uncertainty. Our results indicate that `state-of-the-art' choice models of decisions from description, by failing to consider the intrinsic variability of human choice behavior, find themselves in the odd position of predicting humans' choices better than the same humans' own previous choices for the same problem. We conclude with observations on how the predicament we empirically demonstrate in our work could be handled in the practice of supervised learning.

Selective Integration: An Attentional Theory of Choice Biases and Adaptive Choice

2019 ◽  
Vol 28 (6) ◽  
pp. 552-559 ◽  
Author(s):  
Marius Usher ◽  
Konstantinos Tsetsos ◽  
Moshe Glickman ◽  
Nick Chater
Keyword(s):  
Choice Behavior ◽  
Explicit Model ◽  
Human Choice ◽  
Related Information ◽  
Binary Choices ◽  
Adaptive Choice ◽  
Standard Models ◽  
Attentional Theory ◽  
Consistent Information ◽  
Selective Integration

Human choice behavior shows a range of puzzling anomalies. Even simple binary choices are modified by accept/reject framing and by the presence of decoy options, and they can exhibit circular (i.e., intransitive) patterns of preferences. Each of these phenomena is incompatible with many standard models of choice but may provide crucial clues concerning the elementary mental processes underpinning our choices. One promising theoretical account proposes that choice-related information is selectively gathered through an attentionally limited window favoring goal-consistent information. We review research showing attentional-mediated choice biases and present a computationally explicit model—selective integration—that accounts for these biases.

scholarly journals Application of Quantum—Markov Open System Models to Human Cognition and Decision

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 990
Author(s):  
Jerome Busemeyer ◽  
Qizi Zhang ◽  
S. N. Balakrishnan ◽  
Zheng Wang
Keyword(s):  
Random Walk ◽  
Open System ◽  
Choice Behavior ◽  
Quantum Walk ◽  
Decision Time ◽  
Human Cognition ◽  
System Models ◽  
Human Choice ◽  
Single Process ◽  
Good Potential

Markov processes, such as random walk models, have been successfully used by cognitive and neural scientists to model human choice behavior and decision time for over 50 years. Recently, quantum walk models have been introduced as an alternative way to model the dynamics of human choice and confidence across time. Empirical evidence points to the need for both types of processes, and open system models provide a way to incorporate them both into a single process. However, some of the constraints required by open system models present challenges for achieving this goal. The purpose of this article is to address these challenges and formulate open system models that have good potential to make important advancements in cognitive science.

scholarly journals Goal Side Selection of Penalty Shots in Soccer: A Laboratory Study and Analyses of Men’s World Cup Shoot-Outs

2021 ◽  
pp. 003151252110254
Author(s):  
Mauro R. Pereira ◽  
Geoffrey R. Patching
Keyword(s):  
Laboratory Study ◽  
Choice Behavior ◽  
Lateral Position ◽  
Good Strategy ◽  
World Cup ◽  
Human Choice ◽  
The Right ◽  
Realistic Images ◽  
Selection Of ◽  
Viewing Position

Penalty kicks in soccer provide a unique scenario in which to examine human choice behavior under competitive conditions. Here, we report two studies examining the tendency for soccer kickers to select the goal side with the largest area to the left or right of the goalkeeper’s veridical midline, when the goalkeeper stands marginally off-center. In Study I participants viewed realistic images of a soccer goal and goalkeeper with instructions to choose the left or right side of the goalmouth to best score a goal. We systematically displaced the goalkeeper’s position along the goal line; and, to simulate changes in the kicker’s viewing position, we systematically displaced the lateral position of the goalmouth in each image. While, overall, participants tended to choose the left over the right goal side, this preference was modulated by the goalkeeper’s position relative to the center of the goal and jointly on the lateral position of the goalmouth relative to the participants’ body midline. In Study II we analyzed 100 penalty shots from men’s world cup shoot-outs between the years 1982 to 2018. Again, we found a small tendency for kickers to aim the ball to the left goal side, but with barely any modulating effect of changes in the goalkeeper’s position and no effect of changes in the kicker’s position. In contrast to earlier claims that a goalkeeper may benefit by standing marginally to the left or right of the center of the goal to influence the direction of the kicker’s shot, our findings suggest that this is probably not a good strategy in elite football competitions.

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