scholarly journals Fixation patterns in simple choice reflect optimal information sampling

2019 ◽  
Author(s):  
Frederick Callaway ◽  
Antonio Rangel ◽  
Tom Griffiths
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Sequential Sampling ◽  
Empirical Work ◽  
Reaction Times ◽  
Optimal Solution ◽  
Cognitive Resources ◽  
Human Decision ◽  
Information Sampling ◽  
Optimal Information

When faced with a decision between several options, people rarely fully consider every alternative. Instead, we direct our attention to the most promising candidates, focusing our limited cognitive resources on evaluating the options that we are most likely to choose. A growing body of empirical work has shown that attention plays an important role in human decision making, but it is still unclear how people choose with option to attend to at each moment in the decision making process. In this paper, we present an analysis of how a rational decision maker should allocate her attention. We cast attention allocation in decision making as a sequential sampling problem, in which the decision maker iteratively selects from which distribution to sample in order to update her beliefs about the values of the available alternatives. By approximating the optimal solution to this problem, we derive a model in which both the selection and integration of evidence are rational. This model predicts choices and reaction times, as well as sequences of visual fixations. Applying the model to a ternary-choice dataset, we find that its predictions align well with human data.

scholarly journals Stochastic representation decision theory: How probabilities and values are entangled dual characteristics in cognitive processes

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243661
Author(s):  
Giuseppe M. Ferro ◽  
Didier Sornette
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Time Pressure ◽  
Rational Expectation ◽  
Weighting Function ◽  
Objective Probability ◽  
Decision Making Process ◽  
Stochastic Representation ◽  
Human Decision ◽  
Expectation Theory

Humans are notoriously bad at understanding probabilities, exhibiting a host of biases and distortions that are context dependent. This has serious consequences on how we assess risks and make decisions. Several theories have been developed to replace the normative rational expectation theory at the foundation of economics. These approaches essentially assume that (subjective) probabilities weight multiplicatively the utilities of the alternatives offered to the decision maker, although evidence suggest that probability weights and utilities are often not separable in the mind of the decision maker. In this context, we introduce a simple and efficient framework on how to describe the inherently probabilistic human decision-making process, based on a representation of the deliberation activity leading to a choice through stochastic processes, the simplest of which is a random walk. Our model leads naturally to the hypothesis that probabilities and utilities are entangled dual characteristics of the real human decision making process. It predicts the famous fourfold pattern of risk preferences. Through the analysis of choice probabilities, it is possible to identify two previously postulated features of prospect theory: the inverse S-shaped subjective probability as a function of the objective probability and risk-seeking behavior in the loss domain. It also predicts observed violations of stochastic dominance, while it does not when the dominance is “evident”. Extending the model to account for human finite deliberation time and the effect of time pressure on choice, it provides other sound predictions: inverse relation between choice probability and response time, preference reversal with time pressure, and an inverse double-S-shaped probability weighting function. Our theory, which offers many more predictions for future tests, has strong implications for psychology, economics and artificial intelligence.

scholarly journals Equal evidence perceptual tasks suggest key role for interactive competition in decision-making

2019 ◽  
Author(s):  
Ryan Kirkpatrick ◽  
Brandon Turner ◽  
Per B. Sederberg
Keyword(s):  
Decision Making ◽  
Response Times ◽  
Sequential Sampling ◽  
The Past ◽  
Human Decision ◽  
Complex Decision Making ◽  
Complex Decision ◽  
The Difference ◽  
Best Fit ◽  
Made In

The dynamics of decision-making have been widely studied over the past several decades through the lens of an overarching theory called sequential sampling theory (SST). Within SST, choices are represented as accumulators, each of which races toward a decision boundary by drawing stochastic samples of evidence through time. Although progress has been made in understanding how decisionsare made within the SST framework, considerable debate centers on whether the accumulators exhibit dependency during the evidence accumulation process; namely whether accumulators are independent, fully dependent, or partially dependent. To evaluate which type of dependency is the most plausible representation of human decision-making, we applied a novel twist on two classic perceptual tasks; namely, in addition to the classic paradigm (i.e., the unequal-evidence conditions), we used stimuli that provided different magnitudes of equal-evidence (i.e., the equal-evidence conditions). In equal-evidence conditions, response times systematically decreased with increases in the magnitude of evidence, whereas in unequal evidence conditions, response times systematically increased as the difference in evidence between the two alternatives decreased. We designed a spectrum of models that ranged from independent accumulation to fully dependent accumulation, while also examining the effects of within-trial and between-trial variability. We then fit the set of models to our two experiments and found that models instantiating the principles of partial dependency provided the best fit to the data. Our results further suggest that mechanisms inducing partial dependency, such as lateral inhibition, are beneficial for understanding complex decision-making dynamics, even when the task is relatively simple.

scholarly journals Information and Communication in Organizations

2019 ◽  
Vol 109 ◽  
pp. 545-549 ◽  
Author(s):  
Inga Deimen ◽  
DezsÖ Szalay
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Design Problem ◽  
Information Structure ◽  
Information Design ◽  
Communication In Organizations ◽  
Information And Communication ◽  
Optimal Information

We study a constrained information design problem in an organization. A designer chooses the information structure. A sender with preferences different from the decision-maker observes and processes the information before he communicates with the decision-maker. Information shapes conflicts within the organization: the optimal information structure essentially eliminates conflicts and serves as a substitute to the allocation of decision-making authority in the organization.

Decision Confidence and Uncertainty in Diffusion Models with Partially Correlated Neuronal Integrators

2010 ◽  
Vol 22 (7) ◽  
pp. 1786-1811 ◽  
Author(s):  
Rubén Moreno-Bote
Keyword(s):  
Decision Making ◽  
Exact Solution ◽  
Reaction Times ◽  
Decision Time ◽  
Diffusion Models ◽  
Time Varying ◽  
Decision Confidence ◽  
Human Decision ◽  
Decision Boundaries ◽  
Natural Description

Diffusion models have become essential for describing the performance and statistics of reaction times in human decision making. Despite their success, it is not known how to evaluate decision confidence from them. I introduce a broader class of models consisting of two partially correlated neuronal integrators with arbitrarily time-varying decision boundaries that allow a natural description of confidence. The dependence of decision confidence on the state of the losing integrator, decision time, time-varying boundaries, and correlations is analytically described. The marginal confidence is computed for the half-anticorrelated case using the exact solution of the diffusion process with constant boundaries and compared to that of the independent and completely anticorrelated cases.

scholarly journals Incremental Decision Making Under Risk with the Weighted Expected Utility Model

2017 ◽  
Author(s):  
Hugo Gilbert ◽  
Nawal Benabbou ◽  
Patrice Perny ◽  
Olivier Spanjaard ◽  
Paolo Viappiani
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Expected Utility ◽  
Optimal Solution ◽  
Experimental Results ◽  
Utility Model ◽  
Decision Making Under Risk ◽  
Elicitation Procedure ◽  
Expected Utility Model

This paper deals with decision making under risk with the Weighted Expected Utility (WEU) model, which is a model generalizing expected utility and providing stronger descriptive possibilities. We address the problem of identifying, within a given set of lotteries, a (near-)optimal solution for a given decision maker consistent with the WEU theory. The WEU model is parameterized by two real-valued functions. We propose here a new incremental elicitation procedure to progressively reduce the imprecision about these functions until a robust decision can be made. We also give experimental results showing the practical efficiency of our method.

The Mythical Decision Maker

2011 ◽  
pp. 653-660 ◽  
Author(s):  
Csaba Csáki
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Maker ◽  
Support Systems ◽  
Historical Context ◽  
Decision Makers ◽  
Organizational Decision Making ◽  
Theoretical Investigations ◽  
Human Decision ◽  
History Of

During the history of decision support systems (DSSs)— in fact, during the history of theoretical investigations of human decision-making situations—the decision maker (DM) has been the centre of attention who considers options and makes a choice. However, the notion and definitions of this decision maker, as well as the various roles surrounding his or her activity, have changed depending on both time and scientific areas. Reading the DSS literature, one might encounter references to such players as decision makers, problem owners, stakeholders, facilitators, developers, users, project champions, and supporters, and the list goes on. Who are these players, what is their role, and where do these terms come from? This article presents a review in historical context of some key interpretations aimed at identifying the various roles that actors may assume in an organizational decision-making situation.

Listening Fast and Slow

2021 ◽  
pp. 172-188
Author(s):  
Graham Bodie ◽  
Susanne M. Jones
Keyword(s):  
Social Psychology ◽  
Decision Making ◽  
Information Processing ◽  
Communication Theory ◽  
Dual Process ◽  
Cognitive Resources ◽  
Passive Mode ◽  
Process Framework ◽  
Human Decision ◽  
Listening Process

Like other constructs studied by communication scientists, listening has been viewed as a predominantly deliberate process that requires considerable cognitive resources to perform well. Listening, contrasted with hearing as a more passive mode of information processing, requires a person to actively receive, process, and sensibly respond to aural information. The emphasis on deliberate processing might perhaps have been fueled by research in social psychology, from which much communication theory is drawn. That literature has emphasized rational, deliberate processing at the expense of a more intuitive mode that tends to be viewed as inferior in human decision making and grounded much more in emotions. Using a general dual-process framework, the authors argue that an intuitive, experiential system plays a much more important role in the listening process than previously recognized. They lay out their rationale and model for experiential listening and discuss ways in which people can improve their intuitive listening through mindfulness-based metacognitive practices.

Multistage decision approach for short life cycle products using Pythagorean fuzzy set

2021 ◽  
Vol 40 (1) ◽  
pp. 1343-1356
Author(s):  
Aamir Mahboob ◽  
Tabasam Rashid
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Decision Maker ◽  
Optimal Solution ◽  
Possibility Theory ◽  
Pythagorean Fuzzy Set ◽  
Pythagorean Fuzzy Sets ◽  
Decision Points ◽  
Uncertain Theory ◽  
Topsis Technique

 In this paper, a multistage decision-making problem concerning uncertainty and ambiguity is discussed using Pythagorean fuzzy sets. Complement Pythagorean fuzzy membership grades and their properties are also considered. Using the definition of an alpha-level set, we introduce the multistage decision-making problems, where the possibility theory and satisfaction grades are declared with the help of Pythagorean membership grades. Pythagorean multistage decision-making is an uncertain theory, where decision-maker has only one opportunity to choose the scenario under the combination of Pythagorean possibility and satisfaction grades at each stage. According to the selection of criteria, a series of decision points are concluded. The payoff collaborates with these decision points at each stage. The multistage decision-making using Pythagorean fuzzy sets is the scenario-based theory in place of other theories like lottery-based theory etc. The results have been calculated using multistage Pythagorean fuzzy sets in which the decision-maker has only one chance to select the optimal solution. The TOPSIS technique has been applied and the comparison between these two techniques is highlighted.

Cooperative Human-Computer Decision Making: An Experiment and Some Design Implications

1994 ◽  
Vol 38 (4) ◽  
pp. 220-224 ◽  
Author(s):  
Gunilla A. Sundström ◽  
Anthony C. Salvador
Keyword(s):  
Decision Making ◽  
Fault Diagnosis ◽  
Decision Maker ◽  
Confidence Level ◽  
Intelligent Agents ◽  
Network Performance ◽  
Wrong Decision ◽  
Human Decision ◽  
Types Of Information ◽  
High Level

Creating useful dialogues between human and automated decision makers (i.e., intelligent agents) is a critical design aspect of any effective decision support environment. However, surprisingly few studies have examined the various factors influencing the way a human decision maker interacts with various types of intelligent agents. In the present work, one such factor was examined, namely the confidence expressed by the agent about its own conclusions. Subjects were trained in a network management fault diagnosis task. They were then asked to accept or reject a fault diagnosis generated by the automated decision making agent. The automated decision maker presented its fault diagnosis with an associated confidence indication expressed as a probability. Subjects were required to decide whether to accept or reject the automated decision maker's diagnosis. To conceive an informed response, subjects were able to examine various types of information related to network performance. The results indicated that the higher the confidence level presented by the automated decision maker, the more likely it was that the human decision maker would accept the automatically generated diagnosis. Thus, the higher the confidence level of the automated decision maker, the more likely subjects were to accept a wrong decision. Moreover, subjects examined fewer pieces of information in situations when the automated decision maker expressed a high level of confidence.

scholarly journals On the Irrationality of Being in Two Minds

Entropy ◽  
2020 ◽  
Vol 22 (2) ◽  
pp. 174 ◽  
Author(s):  
Shahram Dehdashti ◽  
Lauren Fell ◽  
Peter Bruza
Keyword(s):  
Decision Making ◽  
Probability Theory ◽  
Quantum Mechanics ◽  
Decision Maker ◽  
General Framework ◽  
Decision Making Under Uncertainty ◽  
Rational Decision ◽  
Rational Decision Making ◽  
Accessible Information ◽  
Human Decision

This article presents a general framework that allows irrational decision making to be theoretically investigated and simulated. Rationality in human decision making under uncertainty is normatively prescribed by the axioms of probability theory in order to maximize utility. However, substantial literature from psychology and cognitive science shows that human decisions regularly deviate from these axioms. Bistable probabilities are proposed as a principled and straight forward means for modeling (ir)rational decision making, which occurs when a decision maker is in “two minds”. We show that bistable probabilities can be formalized by positive-operator-valued projections in quantum mechanics. We found that (1) irrational decision making necessarily involves a wider spectrum of causal relationships than rational decision making, (2) the accessible information turns out to be greater in irrational decision making when compared to rational decision making, and (3) irrational decision making is quantum-like because it violates the Bell–Wigner polytope.

Sign in / Sign up

Export Citation Format

Share Document