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.

Introduction

2018 ◽  
pp. 3-22
Author(s):  
Barry Hoffmaster ◽  
Cliff Hooker
Keyword(s):  
Decision Making ◽  
At Risk ◽  
Problem Solving ◽  
Genetic Counselling ◽  
Expected Utility ◽  
Rational Decision ◽  
Genetic Condition ◽  
Affected Child ◽  
Rational Decision Making ◽  
Formal Rationality

An example of real decision making is presented to illustrate two different accounts of rationality. Women who are at risk of having a child with a genetic condition must decide, after receiving genetic counselling, whether they will try to get pregnant. The genetic counsellors believe the women should use the principle of maximizing expected utility – multiply the probabilities of the outcomes (provided by geneticists) with the values of those outcomes (provided by each woman) and choose the option with the greatest expected utility. This principle manifests the formal rationality of moral philosophy. The women discarded it, however, because they knew that, regardless of the probability, they could have an affected child. Instead, they imagined scenarios of what it could be like living with an affected child to assess whether they could be able to live with their worst scenarios. The process of deliberation these women used to make their decisions is eminently rational, an exemplar of non-formal rationality. This book is about the rationality of deliberation and the judgments that result. The lesson is that we can only appreciate intelligent problem solving in ethics if we embrace a richer, more expansive conception of rational decision making.

Decision of the Wind Power Projects Based on Cost-Efficient Method

2012 ◽  
Vol 246-247 ◽  
pp. 551-555
Author(s):  
Hong Gao ◽  
Wu Gao ◽  
Guo Lu
Keyword(s):  
Decision Making ◽  
Cost Effectiveness ◽  
Wind Power ◽  
Decision Makers ◽  
Life Cycle Costs ◽  
Rational Decision ◽  
Final Project ◽  
Rational Decision Making ◽  
Cost Efficient ◽  
Rational Conclusion

To start from the investment characteristics of wind power projects, account for wind power projects in the life-cycle costs and project income, decision analysis and application of cost-effectiveness of wind power projects, the final project decision makers come to the scientific and rational decision-making program. To carry out the analysis of the case by cost-effectiveness, then come to a scientific and rational conclusion.

scholarly journals Risky-choice framing and rational decision-making

2021 ◽  
Author(s):  
Sarah A. Fisher ◽  
David R. Mandel
Keyword(s):  
Decision Making ◽  
Framing Effects ◽  
Psychological Research ◽  
Risky Choice ◽  
Decision Makers ◽  
Future Research ◽  
Rational Decision ◽  
Rational Decision Making ◽  
Choice Framing

This article surveys the latest research on risky-choice framing effects, focusing on the implications for rational decision-making. An influential program of psychological research suggests that people’s judgements and decisions depend on the way in which information is presented, or ‘framed’. In a central choice paradigm, decision-makers seem to adopt different preferences, and different attitudes to risk, depending on whether the options specify the number of people who will be saved or the corresponding number who will die. It is standardly assumed that such responses violate a foundational tenet of rational decision-making, known as the principle of description invariance. We discuss recent theoretical and empirical research that challenges the dominant ‘irrationalist’ narrative. These approaches typically pay close attention to how decision-makers represent decision problems (including their interpretation of numerical quantifiers or predicate choice) and they highlight the need for a more robust characterization of the description invariance principle. We conclude by indicating avenues for future research that could bring us closer to a complete – and potentially rationalizing – explanation of framing effects.

scholarly journals Teaching & Learning Guide for: Risky-choice framing and rational decision-making

2021 ◽  
Author(s):  
Sarah A. Fisher ◽  
David R. Mandel
Keyword(s):  
Decision Making ◽  
Psychological Research ◽  
Risky Choice ◽  
Decision Makers ◽  
Rational Decision ◽  
Rational Decision Making ◽  
Alternative Approaches ◽  
Learning Guide ◽  
Choice Framing

An influential program of psychological research suggests that people’s judgements and decisions depend on the way in which information is presented, or ‘framed’. In a central choice paradigm, decision-makers seem to adopt different preferences, and different attitudes to risk, depending on whether the options specify the number of people who will be saved or the corresponding number who will die. It is standardly assumed that such responses violate a foundational tenet of rational decision-making, known as the principle of description invariance. However, recent theoretical and empirical research has begun to challenge the dominant ‘irrationalist’ narrative. The alternative approaches being developed typically pay close attention to how decision- makers represent decision problems (including their interpretation of numerical quantifiers or predicate choice). They also highlight the need for a more robust characterization of the description invariance principle itself.

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.

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.

The Economists’ Orthodoxy: Expected Utility Theory

2019 ◽  
pp. 9-18
Author(s):  
Richard Pettigrew
Keyword(s):  
Decision Making ◽  
Expected Utility ◽  
Utility Theory ◽  
Expected Utility Theory ◽  
Rational Decision ◽  
Rational Decision Making ◽  
The World ◽  
Orthodox Theory

This chapter provides an introduction to expected utility theory, the orthodox theory of rational decision-making. It introduces the framework of states of the world, credences, utilities, expected utilities, and preferences. The chapter distinguishes two interpretations of expected utility theory: the realist and the constructivist. It argues in favour of realism and explains that this will be assumed throughout the book. It describes how the problem of choosing for changing selves arises in the theory described here.

Consequence and Utility Modeling in Rational Decision Making

2004 ◽  
Author(s):  
Marc A. Maes ◽  
Michael H. Faber ◽  
Sherif S. Abdelatif
Keyword(s):  
Decision Making ◽  
Utility Functions ◽  
Decision Makers ◽  
Rational Decision ◽  
Rational Decision Making ◽  
Large Structures ◽  
Utility Optimization ◽  
Definition Of ◽  
Cascade Effects

Offshore design and risk assessment are typically marked by far-reaching choices and important one-time decisions. Decision analysis involving large structures, sensitive environments, and difficult operations, requires a very careful formulation of utility and consequences. It is shown in this paper that one of the most important shortcomings of such analyses stems from an incomplete definition of the system, and from the failure to include various “follow-up” consequences. “Follow-up” consequences are, generally speaking, triggered by extreme losses, such as excessive business losses, consequences from unexpected cascade effects, collateral and indirect losses, or other intangible losses. The non-inclusion of such losses occurs either voluntarily or involuntarily. Often the identification and the valuation of follow-up consequences can be prohibitively difficult. For such cases, it is possible to use a simple model based on risk aversion to the consequences associated with extreme discrete hazards during the lifetime of a system. This model is developed in the framework of a lifecycle utility optimization. To add practical value to this model, we also introduce the concept of a Bayesian updating of utility functions. Since utility functions are all about expressing the preferences of expert decision makers, we refer to the Bayesian parameters as “preference” parameters. The paper shows that the approaches developed lead to better and more risk-consistent decision making. An illustrative example is given in the paper, highlighting the significance of the findings.

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