scholarly journals Information processing by networks of quantum decision makers

2018 ◽  
Vol 492 ◽  
pp. 747-766 ◽  
Author(s):  
V.I. Yukalov ◽  
E.P. Yukalova ◽  
D. Sornette
Keyword(s):  
Information Processing ◽  
Decision Makers

Frameworks and Models in Decision-Making and Judgment in Child Welfare and Protection

2020 ◽  
pp. 3-26
Author(s):  
Rami Benbenishty ◽  
John D. Fluke
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Child Welfare ◽  
False Negative ◽  
Real Life ◽  
Decision Makers ◽  
Future Research ◽  
Theoretical Perspectives ◽  
Specificity And Sensitivity ◽  
Predictive Risk

This chapter presents the basic concepts, theoretical perspectives, and areas of scholarship that bear on decisions in child welfare—making choices in decision environments characterized by high levels of uncertainty. The authors distinguish between normative models that predict what decision-makers ought to choose when faced with alternatives and descriptive models that describe how they tend to make these choices in real life. The chapter reviews those challenges that may be especially relevant in the complex context of child welfare and protection. One way in which decision-makers overcome task complexities and limitations in human information processing (bounded rationality) is by using heuristics to navigate complex tasks. The chapter reviews strategies to correct some limitations in judgment. The authors examine the relationships between workers’ predictions of what would be the outcomes of the case and the actual outcomes and describe two types of error (false positive and false negative) and the related concepts of specificity and sensitivity. These issues are followed by a description of the Lens Model and some of its implications for child welfare decision-making, including predictive risk modeling and studies on information processing models. The final section presents current theoretical models in child welfare decision-making and describes Decision-Making Ecology (DME) and Judgments and Decision Processes in Context (JUDPiC). The chapter concludes with suggestions for future research on child welfare decision-making that could contribute to our conceptual understanding and have practical utility as well.

scholarly journals Information Processing and Limited Liability

2012 ◽  
Vol 102 (3) ◽  
pp. 30-34 ◽  
Author(s):  
Bartosz Maćkowiak ◽  
Mirko Wiederholt
Keyword(s):  
Information Processing ◽  
Limited Liability ◽  
Decision Makers ◽  
Good Decision ◽  
Two Agents ◽  
Unlimited Liability

Decision-makers often face limited liability and thus know that their loss will be bounded. We study how limited liability affects the behavior of an agent who chooses how much information to acquire and process in order to take a good decision. We find that an agent facing limited liability processes less information than an agent with unlimited liability. The informational gap between the two agents is larger in bad times than in good times and when information is more costly to process.

scholarly journals Do People Exploit Risk–Reward Structures To Simplify Information Processing in Risky Choice?

2018 ◽  
Author(s):  
Christina Leuker ◽  
Thorsten Pachur ◽  
Ralph Hertwig ◽  
Timothy Joseph Pleskac
Keyword(s):  
Information Processing ◽  
Eye Movements ◽  
Cognitive Processing ◽  
Risky Choice ◽  
Choice Task ◽  
Decision Makers ◽  
The Other ◽  
Value Maximization ◽  
Environmental Property ◽  
Eye Fixations

The high rewards people desire are often unlikely. Here, we investigated whether decision makers exploit such ecological correlations between risks and rewards to simplify theirinformation processing. In a learning phase, participants were exposed to options in which risks and rewards were negatively correlated, positively correlated, or uncorrelated. In a subsequent risky choice task, where the emphasis was on making either a ’fast’ or the ’best’ possible choice, participants’ eye movements were tracked. The changes in the number, distribution, and direction of eye fixations in ’fast’ trials did not differ between the risk–reward conditions. In ’best’ trials, however, participants in the negatively correlated condition lowered their evidence threshold, responded faster, and deviated from expected value maximization more than in the other risk–reward conditions. The results underscore how conclusions about people’s cognitive processing in risky choice can depend on risk–reward structures, an often neglected environmental property.

scholarly journals Data Quality, Power, And Politics: Analysis Of Strategic Decision Making

2011 ◽  
Vol 1 (7) ◽  
Author(s):  
Andrew B. Nyaboga ◽  
Muroki F. Mwaura
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Data Quality ◽  
Decision Maker ◽  
Decision Makers ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Rational Behavior ◽  
The Way

Most decision makers have biases that are inherent the way they seek information, estimate the outcomes, and attach values to outcomes that produce rational behavior. Many aspects of decision-making may not be accurate because of information processing limitations, power and politics. This paper presents a set of ideas, models, and limitations caused by biases of a decision maker when sorting information.

scholarly journals Over-representation of extreme events in decision-making reflects rational use of cognitive resources

2016 ◽  
Author(s):  
Falk Lieder ◽  
Tom Griffiths ◽  
Ming Hsu
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Expected Utility ◽  
Extreme Events ◽  
Finite Time ◽  
Cognitive Biases ◽  
Decision Makers ◽  
Cognitive Resources ◽  
Memory Recall ◽  
Wide Range

People’s decisions and judgments are disproportionately swayed by improbable but extreme eventualities, such as terrorism, that come to mind easily. This article explores whether such availability biases can be reconciled with rational information processing by taking into account the fact that decision-makers value their time and have limited cognitive resources. Our analysis suggests that to make optimal use of their finite time decision-makers should over-represent the most important potential consequences relative to less important, put potentially more probable, outcomes. To evaluate this account we derive and test a model we call utility-weighted sampling. Utility-weighted sampling estimates the expected utility of potential actions by simulating their outcomes. Critically, outcomes with more extreme utilities have a higher probability of being simulated. We demonstrate that this model can explain not only people’s availability bias in judging the frequency of extreme events but also a wide range of cognitive biases in decisions from experience, decisions from description, and memory recall.

Development and Evaluation of an Information Management Training Program

2002 ◽  
Vol 46 (25) ◽  
pp. 2012-2016
Author(s):  
Eileen B. Entin ◽  
Elliot E. Entin ◽  
Kathleen P. Hess
Keyword(s):  
Information Processing ◽  
Training Program ◽  
Information Management ◽  
Information Needs ◽  
Applied Research ◽  
Management Training ◽  
Organizational Knowledge ◽  
Decision Makers ◽  
Management Skills ◽  
Situation Assessment

Effective information management skills are critical as we become more and more inundated with huge amounts of information. Drawing on applied research on information processing and situation assessment, we designed an information management training program based on the premises that 1) training in the identification of one's own information requirements will help decision makers recognize their critical information needs and focus on needed rather than surplus information, and 2) enhancement of organizational knowledge will provide decision makers with a clearer understanding of the needs and capabilities of other nodes in the organization. We developed an information management training program comprised of written and demonstration materials based on the mnemonic MISSION that was designed to help individuals identify and focus on the information needs for their mission and tasks. We conducted an evaluation of the training program and concluded that we needed to focus more strongly on behavioral rather than conceptual components of information processing. We also concluded that, to be useful, organizational knowledge needs to be integrated with the information management training.

Information Processing Techniques: A Major Asset for the Aging and Life Management of Key NPP Components

2005 ◽  
Author(s):  
V. E. Just ◽  
B. Ricard ◽  
L. Chatellier ◽  
L. Fournier ◽  
P. Hai¨k
Keyword(s):  
Information Processing ◽  
Investment Strategy ◽  
Decision Makers ◽  
Condition Based Maintenance ◽  
Economic Point ◽  
Life Management ◽  
Knowledge Based ◽  
Processing Techniques ◽  
The Impact

The life management of a nuclear power plant raises several major issues amongst which ranks the aging management of the key components of the plant, both from a technical and an economic point of view. Decision-makers are thus faced with the need to define the best strategy in order to achieve the best possible performance while meeting all regulatory requirements. EDF R&D is therefore deeply involved in developing advanced decision-making support tools so the EDF Engineering and Generation Divisions can optimize the long-term management of NPP components. In this paper we wish to provide the reader with an overview of how advanced information processing techniques such as signal and image processing algorithms and knowledge-based information systems recently contributed to the improvement of in-service inspections, condition-based maintenance, and asset management. First we focus on how multi-dimensional image reconstruction techniques increase component durability as they dramatically improve defect positioning and sizing when applied to radiographic data or ultrasonic data. We then detail current research work regarding the development of next generation prognostics systems which allow condition-based maintenance to take simultaneously into account monitoring data (for early fault detection), time-dependent aging models (for degradation kinetics), expert opinion as well as a quantified evaluation of the impact (on reliability and costs) of every potential decision. Lastly we describe how knowledge-based systems can help top level decision-makers get a transverse, long-term view on how a life-management investment strategy translates into plant availability, avoided costs and improved component durability.

scholarly journals Thermodynamics as a theory of decision-making with information-processing costs

2013 ◽  
Vol 469 (2153) ◽  
pp. 20120683 ◽  
Author(s):  
Pedro A. Ortega ◽  
Daniel A. Braun
Keyword(s):  
Decision Making ◽  
Free Energy ◽  
Information Processing ◽  
Expected Utility ◽  
Statistical Physics ◽  
Variational Principles ◽  
Decision Makers ◽  
Rational Decision ◽  
Rational Decision Making ◽  
Human Decision

Perfectly rational decision-makers maximize expected utility, but crucially ignore the resource costs incurred when determining optimal actions. Here, we propose a thermodynamically inspired formalization of bounded rational decision-making where information processing is modelled as state changes in thermodynamic systems that can be quantified by differences in free energy. By optimizing a free energy, bounded rational decision-makers trade off expected utility gains and information-processing costs measured by the relative entropy. As a result, the bounded rational decision-making problem can be rephrased in terms of well-known variational principles from statistical physics. In the limit when computational costs are ignored, the maximum expected utility principle is recovered. We discuss links to existing decision-making frameworks and applications to human decision-making experiments that are at odds with expected utility theory. Since most of the mathematical machinery can be borrowed from statistical physics, the main contribution is to re-interpret the formalism of thermodynamic free-energy differences in terms of bounded rational decision-making and to discuss its relationship to human decision-making experiments.

scholarly journals Give credit to the market: The decision not to prohibit 100 per cent loan-to-value mortgages

2019 ◽  
Vol 67 (2) ◽  
pp. 25-45
Author(s):  
Cathal FitzGerald
Keyword(s):  
Information Processing ◽  
High Risk ◽  
Critical Time ◽  
Decision Makers ◽  
Institutional Factors ◽  
Suboptimal Outcome ◽  
Institutional Actors ◽  
Ideological Context ◽  
Market Ideology

AbstractA decision not to prohibit or limit high-risk mortgage products in Ireland in 2005 reveals the extent to which three important factors – interests, institutions, ideology – impact on information processing by decision-makers, and reveals irrationality or otherwise in the process. This article summarises the events leading up to the bad decision on 100 per cent loan-to-value (LTV) mortgages in November 2005. This case reveals the nature of the interaction between government departments, regulators and banks at a critical time before the crash, and shows how a department’s interests can interact with institutional factors, and the ideological context, to prompt poor rational and irrational information processing, and lead to a bad decision. In particular, the dominance of a market ideology which raised the threshold for what information was necessary before intervention would be made, combined with the low institutional standing of the department seeking intervention, produced a suboptimal outcome. Finally, the case provides evidence of irrationality (e.g. groupthink, herding) within institutional actors, rather than between them.

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