scholarly journals Empirical evidence for resource-rational anchoring and adjustment

2017 ◽  
Author(s):  
Falk Lieder ◽  
Tom Griffiths ◽  
Quentin J.M. Huys ◽  
Noah D. Goodman
Keyword(s):  
Finite Time ◽  
Initial Guess ◽  
Cognitive Resources ◽  
Rational Use ◽  
Anchoring Bias ◽  
Error Cost ◽  
Cost Of Time ◽  
The Cost ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

People’s estimates of numerical quantities are systematically biased towards their initial guess. This anchoring bias is usually interpreted as sign of human irrationality, but it has recently been suggested that the anchoring bias instead results from people’s rational use of their finite time and limited cognitive resources. If this were true, then adjustment should decrease with the relative cost of time. To test this hypothesis, we designed a new numerical estimation paradigm that controls people’s knowledge and varies the cost of time and error independently while allowing people to invest as much or as little time and effort into refining their estimate as they wish. Two experimentsconfirmed the prediction that adjustment decreases with time cost but increases with error cost regardless of whether the anchor was self-generated or provided. These results support the hypothesis that people rationally adapt their number of adjustments to achieve a near-optimal speed-accuracy tradeoff. This suggests that the anchoring bias might be a signature of the rational use of finite time and limited cognitive resources rather than a sign of human irrationality.

scholarly journals Adaptive integration of habits into depth-limited planning defines a habitual-goal–directed spectrum

2016 ◽  
Vol 113 (45) ◽  
pp. 12868-12873 ◽  
Author(s):  
Mehdi Keramati ◽  
Peter Smittenaar ◽  
Raymond J. Dolan ◽  
Peter Dayan
Keyword(s):  
Decision Making ◽  
Decision Process ◽  
Time Pressure ◽  
Human Subjects ◽  
Mental Simulation ◽  
Adaptive Integration ◽  
Accurate Evaluation ◽  
The Cost ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

Behavioral and neural evidence reveal a prospective goal-directed decision process that relies on mental simulation of the environment, and a retrospective habitual process that caches returns previously garnered from available choices. Artificial systems combine the two by simulating the environment up to some depth and then exploiting habitual values as proxies for consequences that may arise in the further future. Using a three-step task, we provide evidence that human subjects use such a normative plan-until-habit strategy, implying a spectrum of approaches that interpolates between habitual and goal-directed responding. We found that increasing time pressure led to shallower goal-directed planning, suggesting that a speed-accuracy tradeoff controls the depth of planning with deeper search leading to more accurate evaluation, at the cost of slower decision-making. We conclude that subjects integrate habit-based cached values directly into goal-directed evaluations in a normative manner.

scholarly journals The anchoring bias reflects rational use of cognitive resources

2017 ◽  
Vol 25 (1) ◽  
pp. 322-349 ◽  
Author(s):  
Falk Lieder ◽  
Thomas L. Griffiths ◽  
Quentin J. M. Huys ◽  
Noah D. Goodman
Keyword(s):  
Cognitive Resources ◽  
Rational Use ◽  
Anchoring Bias

scholarly journals The anchoring bias reflects rational use of cognitive resources

2017 ◽  
Author(s):  
Falk Lieder ◽  
Tom Griffiths ◽  
Quentin J.M. Huys ◽  
Noah D. Goodman
Keyword(s):  
Process Model ◽  
Cognitive Biases ◽  
Human Mind ◽  
Human Cognition ◽  
Cognitive Resources ◽  
Reasoning Under Uncertainty ◽  
Rational Analysis ◽  
Rational Use ◽  
Wide Range ◽  
Anchoring Bias

Cognitive biases, such as the anchoring bias, pose a serious challenge to rational accounts of human cognition. We investigate whether rational theories can meet this challenge by taking into account the mind’s bounded cognitive resources. We asked what reasoning under uncertainty would look like if people made rational use of their finite time and limited cognitive resources. To answer this question, we applied a mathematical theory of bounded rationality to the problem of numerical estimation. Our analysis led to a rational process model that can be interpreted in terms of anchoring-and-adjustment. This model provided a unifying explanation for ten anchoring phenomena including the differential effect of accuracy motivation on the bias towards provided versus self-generated anchors. Our results illustrate the potential of resource-rational analysis to provide formal theories that can unify a wide range of empirical results and reconcile the impressive capacities of the human mind with its apparently irrational cognitive biases.

scholarly journals Anchoring and Adjustment

2017 ◽  
Author(s):  
Falk Lieder ◽  
Tom Griffiths ◽  
Quentin J.M. Huys ◽  
Noah D. Goodman
Keyword(s):  
Bayesian Model ◽  
Computational Models ◽  
Numerical Estimation ◽  
Time Cost ◽  
Rational Model ◽  
Anchoring And Adjustment ◽  
Technical Report ◽  
Error Cost ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

This technical report compares alternative computational models of numerical estimation using Bayesian model selection. We find that people's estimates are best explained by a resource-rational model of anchoring and adjustment according to which the number of adjustments increases with error cost but decreases with time cost so as to achieve an optimal speed-accuracy tradeoff.

The Neural and Computational Basis of Controlled Speed-Accuracy Tradeoff during Task Performance

2008 ◽  
Vol 20 (11) ◽  
pp. 1952-1965 ◽  
Author(s):  
Vincent van Veen ◽  
Marie K. Krug ◽  
Cameron S. Carter
Keyword(s):  
Response Threshold ◽  
Response Preparation ◽  
Baseline Activity ◽  
Dorsolateral Prefrontal ◽  
The Cost ◽  
Parietal Cortices ◽  
Speed Accuracy ◽  
Premotor Areas ◽  
Accuracy Tradeoff ◽  
At Will

People are capable, at will, of trading speed for accuracy when performing a task; they can focus on performing accurately at the cost of being slow, or emphasize speed at the cost of decreased accuracy. Here, we used functional magnetic resonance imaging to investigate the neural correlates of this ability. We show increased baseline activity during speed emphasis in a network of areas related to response preparation and execution, including the premotor areas of the frontal lobe, the basal ganglia, the thalamus, and the dorsolateral prefrontal and left parietal cortices. Furthermore, speed emphasis was associated with reduced transient response-related activation in several of these structures, suggesting that because of the greater baseline activity under speed emphasis, less activation is needed in these structures to reach response threshold, consistent with the assumptions of several computational theories. Moreover, we identify the dorsolateral prefrontal cortex as providing the top-down control signal that increases this baseline activity.

Neuroticism and Speed-Accuracy Tradeoff in Self-Paced Speeded Mental Addition and Comparison

2010 ◽  
Vol 31 (3) ◽  
pp. 130-137 ◽  
Author(s):  
Hagen C. Flehmig ◽  
Michael B. Steinborn ◽  
Karl Westhoff ◽  
Robert Langner
Keyword(s):  
Reaction Time ◽  
Response Speed ◽  
Time Variability ◽  
Reaction Time Variability ◽  
Comparison Task ◽  
Processing Efficiency ◽  
Mental Addition ◽  
Speed Accuracy ◽  
The Relationship ◽  
Accuracy Tradeoff

Previous research suggests a relationship between neuroticism (N) and the speed-accuracy tradeoff in speeded performance: High-N individuals were observed performing less efficiently than low-N individuals and compensatorily overemphasizing response speed at the expense of accuracy. This study examined N-related performance differences in the serial mental addition and comparison task (SMACT) in 99 individuals, comparing several performance measures (i.e., response speed, accuracy, and variability), retest reliability, and practice effects. N was negatively correlated with mean reaction time but positively correlated with error percentage, indicating that high-N individuals tended to be faster but less accurate in their performance than low-N individuals. The strengthening of the relationship after practice demonstrated the reliability of the findings. There was, however, no relationship between N and distractibility (assessed via measures of reaction time variability). Our main findings are in line with the processing efficiency theory, extending the relationship between N and working style to sustained self-paced speeded mental addition.

Speed/accuracy tradeoff in directed forgetting

1997 ◽  
Author(s):  
Jeffry S. Kellogg ◽  
Xiangen Hu ◽  
William Marks
Keyword(s):  
Directed Forgetting ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

scholarly journals A Constrained Markovian Diffusion Model for Controlling the Pollution Accumulation

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1466
Author(s):  
Beatris Adriana Escobedo-Trujillo ◽  
José Daniel López-Barrientos ◽  
Javier Garrido-Meléndez
Keyword(s):  
Dynamic Programming ◽  
Dirichlet Problem ◽  
Stochastic Control ◽  
Finite Time ◽  
Time Horizon ◽  
Closed Loop ◽  
Programming Techniques ◽  
Pollution Accumulation ◽  
Finite Time Horizon ◽  
The Cost

This work presents a study of a finite-time horizon stochastic control problem with restrictions on both the reward and the cost functions. To this end, it uses standard dynamic programming techniques, and an extension of the classic Lagrange multipliers approach. The coefficients considered here are supposed to be unbounded, and the obtained strategies are of non-stationary closed-loop type. The driving thread of the paper is a sequence of examples on a pollution accumulation model, which is used for the purpose of showing three algorithms for the purpose of replicating the results. There, the reader can find a result on the interchangeability of limits in a Dirichlet problem.

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