The role of social feedback in steady-state performance of human decision making for two-alternative choice tasks

2010 ◽  
Author(s):  
Andrew Stewart ◽  
Naomi Ehrich Leonard
Keyword(s):  
Decision Making ◽  
Steady State ◽  
Social Feedback ◽  
Human Decision ◽  
Alternative Choice ◽  
Choice Tasks ◽  
Steady State Performance

scholarly journals The role of time in human decision-making

2013 ◽  
Vol 13 (9) ◽  
pp. 305-305
Author(s):  
M. Popovic ◽  
M. Lengyel ◽  
J. Fiser
Keyword(s):  
Decision Making ◽  
Human Decision

scholarly journals A map of decoy influence in human multi-alternative choice

2020 ◽  
Author(s):  
Tsvetomira Dumbalska ◽  
Vickie Li ◽  
Konstantinos Tsetsos ◽  
Christopher Summerfield
Keyword(s):  
Decision Making ◽  
Simple Model ◽  
Irrelevant Information ◽  
Incentive Compatible ◽  
Special Cases ◽  
Human Decision ◽  
Human Participants ◽  
Alternative Choice ◽  
Decoy Effects ◽  
Attribute Space

Human decisions can be biased by irrelevant information. For example, choices between two preferred alternatives can be swayed by a third option that is inferior or unavailable. Previous work has identified three classic biases, known as the attraction, similarity and compromise effects, which arise during choices between economic alternatives defined by two attributes. However, the reliability, interrelationship, and computational origin of these three biases has been controversial. Here, a large cohort of human participants made incentive-compatible choices among assets that varied in price and quality. Instead of focusing on the three classic effects, we sampled decoy stimuli exhaustively across bidimensional multi-attribute space and constructed a full map of decoy influence on choices between two otherwise preferred target items. Our analysis revealed that the decoy influence map was highly structured even beyond the three classic biases. We identified a very simple model that can fully reproduce the decoy influence map and capture its variability in individual participants. This model reveals that the three decoy effects are not distinct phenomena but are all special cases of a more general principle, by which attribute values are repulsed away from the context provided by rival options. The model helps understand why the biases are typically correlated across participants and allows us to validate a new prediction about their interrelationship. This work helps to clarify the origin of three of the most widely-studied biases in human decision-making.

scholarly journals The Effects of Situational and Individual Factors on Algorithm Acceptance in COVID-19-Related Decision-Making: A Preregistered Online Experiment

2021 ◽  
Vol 3 ◽  
pp. 27-46
Author(s):  
Sonja Utz ◽  
Lara Wolfers ◽  
Anja Göritz
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Individual Factors ◽  
Online Experiment ◽  
Human Decision ◽  
Attitudes And Knowledge

In times of the COVID-19 pandemic, difficult decisions such as the distribution of ventilators must be made. For many of these decisions, humans could team up with algorithms; however, people often prefer human decision-makers. We examined the role of situational (morality of the scenario; perspective) and individual factors (need for leadership; conventionalism) for algorithm preference in a preregistered online experiment with German adults (n = 1,127). As expected, algorithm preference was lowest in the most moral-laden scenario. The effect of perspective (i.e., decision-makers vs. decision targets) was only significant in the most moral scenario. Need for leadership predicted a stronger algorithm preference, whereas conventionalism was related to weaker algorithm preference. Exploratory analyses revealed that attitudes and knowledge also mattered, stressing the importance of individual factors.

The Role of Executive Function in Shaping Reinforcement Learning

2020 ◽  
Author(s):  
Milena Rmus ◽  
Samuel McDougle ◽  
Anne Collins
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Instrumental Behavior ◽  
Complex Environments ◽  
Neural Computations ◽  
Human Decision ◽  
Brain And Behavior ◽  
And Behavior ◽  
The Brain

Reinforcement learning (RL) models have advanced our understanding of how animals learn and make decisions, and how the brain supports some aspects of learning. However, the neural computations that are explained by RL algorithms fall short of explaining many sophisticated aspects of human decision making, including the generalization of learned information, one-shot learning, and the synthesis of task information in complex environments. Instead, these aspects of instrumental behavior are assumed to be supported by the brain’s executive functions (EF). We review recent findings that highlight the importance of EF in learning. Specifically, we advance the theory that EF sets the stage for canonical RL computations in the brain, providing inputs that broaden their flexibility and applicability. Our theory has important implications for how to interpret RL computations in the brain and behavior.

scholarly journals Domestic dogs' gaze and behavior in 2-alternative choice tasks

2021 ◽  
Author(s):  
Julia Espinosa ◽  
Daphna Buchsbaum
Keyword(s):  
Decision Making ◽  
Visual Discrimination ◽  
Visual Information ◽  
Choice Behavior ◽  
Choice Task ◽  
Domestic Dogs ◽  
The World ◽  
Alternative Choice ◽  
And Behavior ◽  
Choice Tasks

Species such as humans rely on their excellent visual abilities to perceive and navigate the world. Dogs have co-habited with humans for millennia, yet we know little about how they gather and use visual information to guide decision-making. Across five experiments, we presented pet dogs (N=49) with two foods of unequal value in a 2-alternative choice task, and measured whether dogs showed preferential gazing, and whether visual attention patterns were associated with item choice. Overall, dogs looked significantly longer at the preferred (high value) food over the low value alternative. There was also evidence of item-dependent predictive gaze—dogs looked proportionally longer at the item they subsequently chose. Surprisingly, dogs’ choice behavior was only slightly above chance, despite visual discrimination. These results suggest that dogs use visual information in the environment to inform their choice behavior, but that other factors may also contribute to their decision-making.

Complexity, Bounded Rationality and Heuristic Search

2002 ◽  
Vol 1 (1) ◽  
Author(s):  
W. Bentley MacLeod
Keyword(s):  
Decision Making ◽  
Rational Choice ◽  
Heuristic Search ◽  
Rational Choice Theory ◽  
Choice Theory ◽  
Heuristic Function ◽  
Heuristic Search Algorithms ◽  
Human Decision

Abstract This paper explores the use of heuristic search algorithms for modeling human decision making. It is shown that this algorithm is consistent with many observed behavioral regularities, and may help explain deviations from rational choice. The main insight is that the heuristic function can be viewed as formal implementation of one aspect of emotion as discussed in Descarte's Error by Antonio Damasio. Consistent with Damasio's observations, it is shown that the quality of decision making is very sensitive to the nature of the heuristic ("emotion"), and hence this may help us better understand the role of emotion in rational choice theory.

Tactical Considerations1

2020 ◽  
pp. 154-190
Author(s):  
Seth W. Stoughton ◽  
Jeffrey J. Noble ◽  
Geoffrey P. Alpert
Keyword(s):  
Decision Making ◽  
Use Of Force ◽  
Active Shooter ◽  
Community Members ◽  
Human Decision ◽  
Effects Of Stress ◽  
Police Tactics

Officers do not use force in a vacuum. It has long been recognized that a use of force is not the result of a single decision, but rather of “a contingent sequence of decisions and resulting behaviors—each increasing or decreasing the probability of an eventual use of … force.” How officers approach a situation, then, can affect whether and how they use force. Tactics are the techniques and procedures that officers use to protect themselves and community members. This chapter provides a framework for assessing police tactics, then offers an in-depth discussion of core tactical concepts. It explains why time is the single most important tactical consideration, details the effects of stress on human decision making, and illustrates how officers use tactical choices to “create time” and how they can use that time to minimize their need to use force. The chapter concludes by exploring the role of police tactics in three very different situations: arrests, crisis interventions, and active-shooter situations.

Emotions in Offender Decision Making

2017 ◽  
Author(s):  
Jean-Louis van Gelder
Keyword(s):  
Decision Making ◽  
Theoretical Framework ◽  
Cognitive Sciences ◽  
Offending Behavior ◽  
Human Decision ◽  
Understanding Emotions ◽  
Crime Causation

This chapter examines the influence of emotions on offender decision making. It reviews the empirical and theoretical criminological literature on the role of emotions in crime causation but also draws from other disciplines in the behavioral and cognitive sciences that have examined the influence of emotions on human decision making. Specific attention is devoted to appraisal theories of emotion, which, it is argued, provide a useful theoretical framework for studying and understanding emotions in criminal contexts. In doing so, it is shown that criminal decision-making research and theorizing may have so far failed to fully acknowledge the influence of emotions on offending behavior.

Optimal Decision Making on the Basis of Evidence Represented in Spike Trains

2010 ◽  
Vol 22 (5) ◽  
pp. 1113-1148 ◽  
Author(s):  
Jiaxiang Zhang ◽  
Rafal Bogacz
Keyword(s):  
Decision Making ◽  
Spike Trains ◽  
Decision Procedures ◽  
Optimal Decision ◽  
Ratio Test ◽  
Perceptual Decision Making ◽  
Sensory Evidence ◽  
Optimal Decision Making ◽  
Alternative Choice ◽  
Choice Tasks

Experimental data indicate that perceptual decision making involves integration of sensory evidence in certain cortical areas. Theoretical studies have proposed that the computation in neural decision circuits approximates statistically optimal decision procedures (e.g., sequential probability ratio test) that maximize the reward rate in sequential choice tasks. However, these previous studies assumed that the sensory evidence was represented by continuous values from gaussian distributions with the same variance across alternatives. In this article, we make a more realistic assumption that sensory evidence is represented in spike trains described by the Poisson processes, which naturally satisfy the mean-variance relationship observed in sensory neurons. We show that for such a representation, the neural circuits involving cortical integrators and basal ganglia can approximate the optimal decision procedures for two and multiple alternative choice tasks.

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