Formal Decision Theory Research Articles

Decision Theory Unbound

AbstractCountenancing unbounded utility in ethics gives rise to deep puzzles in formal decision theory. Here, these puzzles are taken as an invitation to assess the most fundamental principles relating probability and value, with the aim of demonstrating that unbounded utility in ethics is compatible with a desirable decision theory. The resulting theory frames further discussion of Expected Utility Theory and of principles concerning symmetries of utility.

Bounded rationality, enactive problem solving, and the neuroscience of social interaction.

This article aims to show that there is an alternative way to explain human action with respect to the bottlenecks of the psychology of decision making. The empirical study of human behaviour from mid-20th century to date has mainly developed by looking at a normative model of decision making. In particular Subjective Expected Utility (SEU) decision making, which stems from the subjective expected utility theory of Savage (1954) that itself extended the analysis by Von Neumann and Morgenstern (1944). On this view, the cognitive psychology of decision making precisely reflects the conceptual structure of formal decision theory. This article shows that there is an alternative way to understand decision making by recovering Newell and Simon's account of problem solving, developed in the framework of bounded rationality, and inserting it into the more recent research program of embodied cognition. Herbert Simon emphasized the importance of problem solving and differentiated it from decision making, which he considered a phase downstream of the former. Moreover according to Simon the centre of gravity of the rationality of the action lies in the ability to adapt. And the centre of gravity of adaptation is not so much in the internal environment of the actor as in the pragmatic external environment. The behaviour adapts to external purposes and reveals those characteristics of the system that limit its adaptation. According to Simon (1981), in fact, environmental feedback is the most effective factor in modelling human actions in solving a problem. In addition, his notion of problem space signifies the possible situations to be searched in order to find that situation which corresponds to the solution. Using the language of embodied cognition, the notion of problem space is about the possible solutions that are enacted in relation to environmental affordances. The correspondence between action and the solution of a problem conceptually bypasses the analytic phase of the decision and limits the role of symbolic representation. In solving any problem, the search for the solution corresponds to acting in ways that involve recursive feedback processes leading up to the final action. From this point of view, the new term enactive problem solving summarizes this fusion between bounded and embodied cognition. That problem solving involves bounded cognition means that it is through the problem solver's enactive interaction with environmental affordances, and especially social affordances that it is possible to construct the processes required for arriving at a solution. Lastly the concept of enactive problem solving is also able to explain the mechanisms underlying the adaptive heuristics of rational ecology. Its adaptive function is effective both in practical and motor tasks as well as in abstract and symbolic ones.

Inductive and deductive approaches to modelling of human decision making

This paper presents the two conventional approaches to modelling of human decision making. The inductive approach emphasises the anchoring in empirical data. The deductive approach is based on accepted assumtions from formal decision theory. A comparison of the resulting models show that the outcome is very sirnilar. It is argued that this is because modeiling of decision making basically is a hermeneutical exercise, hence neither purely inductive or deductive. An adequate model of decision making in man-machine systems must be based on a description that captures the complexity of both man and machine, such as Cognitive Systems Engineering. This leads to two essential assumptions about decision making systems, that they must be both causa! and intentional. An alternate cybemetic approach to modeiling of decision making, which includes both of theseassumptions, is briefly described.

The key to the knowledge norm of action is ambiguity

Knowledge-first epistemology includes a knowledge norm of action: roughly, act only on what you know. This norm has been criticized, especially from the perspective of so-called standard decision theory. Mueller and Ross provide example decision problems which seem to show that acting properly cannot require knowledge. I argue that this conclusion depends on applying a particular decision theory (namely, Savage-style Expected Utility Theory) which is ill-motivated in this context. Agents’ knowledge is often most plausibly formalized as an ambiguous epistemic state, and the theory of decision under ambiguity is then the appropriate modeling tool. I show how to model agents as acting rationally on the basis of their knowledge according to such a theory. I conclude that the tension between the knowledge norm of action and formal decision theory is illusory; the knowledge-first paradigm should be used to actively select the decision-theoretical tools that can best capture the knowledge-based decisions in any given situation.

Risk analysis and decision theory: A bridge

The risk-triplet approach pioneered by Kaplan and Garrick is the keystone of operational risk analysis. We perform a sharp embedding of the elements of this framework into the one of formal decision theory, which is mainly concerned with the methodological and modeling issues of decision making. The aim of this exercise is twofold: on the one hand, it gives operational risk analysis a direct access to the rich toolbox that decision theory has developed, in the last decades, in order to deal with complex layers of uncertainty; on the other, it exposes decision theory to the challenges of operational risk analysis, thus providing it with broader scope and new stimuli.

工作记忆负荷对风险决策框架效应的影响

风险决策中的框架效应(Framing Effect)是指由于对同一问题的表达方式不同，导致决策出现偏差的现象。框架效应是由Tversky和Kahneman (1981)在前景理论(Prospect Theory)的基础上提出的，是描述性决策理论反驳规范性决策理论的有力例证。近年来，对风险决策框架效应现象的研究成果颇丰，但针对框架效应内在认知机制的研究却相对贫乏。为进一步揭示风险决策中框架效应的内在机制，本研究在双加工理论的基础上，探讨了工作记忆负荷对框架效应的影响。实验采用2 (积极框架/消极框架) × 2 (无工作记忆负荷/有工作记忆负荷)两因素被试间设计，随机选取陕西师范大学自愿参加实验的80名被试，其中男生32人，女生48人，随机分配到4个小组，每组20人。结果表明：1) 框架类型主效应显著；2) 工作记忆负荷主效应不显著；3) 框架类型与工作记忆负荷之间在P = 0.05水平时交互作用显著。研究表明框架效应的产生需要较多的认知资源，倾向于分析式加工过程。 Tversky and Kahneman (1981) introduced the term framing effect for a decision maker’s repre-sentation of a decision problem including acts outcomes and contingencies associated with dif-ferent alternatives. Framing effect is made up on the basis of prospect theory, which is a typical case of the descriptive decision theory, but violates the formal decision theory. In recent years, the research on the phenomenon of the framing effect is fruitful, but the research of the inner cognitive mechanism of framing effect is relatively poor. In order to further reveal the internal mechanism of effect of framework in risk decision, the study discusses the effect of working memory load on framing effect on the basis of the theory of dual-process, using 2 (positive framing, negative framing) × 2 (working memory load, no working memory load) among subjects experimental design. In the experiment, 32 boys and 48 girls were randomly selected from Shaanxi Normal University, and randomly assigned to four groups, 20 subjects in each group. The results showed that: 1) the main effect of frame type is significant; 2) the main effect of working memory load is not significant; 3) the interaction of frame type and working memory load is significant at P = 0.05 level. Research shows that framing effect needs more cognitive resources; it tends to be an analytical processing procedure.

Toward the integration of personality theory and decision theory in explaining economic behavior: An experimental investigation

Economics and trait-based personality psychology have taken different approaches to understanding individual differences. The former emphasizes variables measured according to formal decision theory; the latter instead emphasizes variables derived from the factor analysis of trait assessments.In a data set on trainee truckers in a large US company, we provide a systematic assessment of the empirical pattern of relationships and correlations between the measurements used in these two approaches by comparing the predictive power of variables derived from personality theory and decision theory for several individual characteristics and outcomes, and relating the two sets of measurements to each other.We show that personality traits have a comparable or stronger statistical predictive power than do economic preferences for several dependent variables, including credit score, job persistence, and heavy truck accidents. They also have strong predictive power for Body Mass Index (BMI) and smoking status. Further, decision theory and personality variables are meaningfully related. For example, we confirm that cognitive ability explains a substantial part of time preferences, and find that Neuroticism and cognitive ability together explain attitudes toward risk. In an experimental game, cognitive skills and Agreeableness explain important aspects of strategic behavior.

Use and Communication of Probabilistic Forecasts.

Probabilistic forecasts are becoming more and more available. How should they be used and communicated? What are the obstacles to their use in practice? I review experience with five problems where probabilistic forecasting played an important role. This leads me to identify five types of potential users: Low Stakes Users, who don't need probabilistic forecasts; General Assessors, who need an overall idea of the uncertainty in the forecast; Change Assessors, who need to know if a change is out of line with expectatations; Risk Avoiders, who wish to limit the risk of an adverse outcome; and Decision Theorists, who quantify their loss function and perform the decision-theoretic calculations. This suggests that it is important to interact with users and to consider their goals. The cognitive research tells us that calibration is important for trust in probability forecasts, and that it is important to match the verbal expression with the task. The cognitive load should be minimized, reducing the probabilistic forecast to a single percentile if appropriate. Probabilities of adverse events and percentiles of the predictive distribution of quantities of interest seem often to be the best way to summarize probabilistic forecasts. Formal decision theory has an important role, but in a limited range of applications.

Justifying precautionary policies: Incommensurability and uncertainty

When decisions are taken in conditions of Keynesian or Knightian uncertainty, and when there is a threat of serious or irreversible environmental damage, the Precautionary Principle is often recommended to guide decision-making. However, the Precautionary Principle has been widely criticised. In response to these criticisms, a qualitative version of the Precautionary Principle is developed which draws its normative content from a blend of formal decision theory and political philosophy. It is argued that precautionary action can be justified by some flexible combination of uncertainty and incommensurability. The ‘greater’ the uncertainty, the ‘less’ incommensurability is required to justify precautionary action, and vice versa. Throughout the paper, the arguments are explored using the example of climate change decision problems.

Toward the Integration of Personality Theory and Decision Theory in the Explanation of Economic and Health Behavior

Trait-based personality psychology and economics have taken different approaches to understanding individual differences, with the former emphasizing variables derived from the factor analysis of trait assessments, and the latter emphasizing variables derived from formal decision theory. In a data set on trainee truckers in a large US company, we provide a systematic initial assessment of the empirical pattern of relationships between the elements from these two approaches by comparing the predictive power of measurements derived from personality theory and decision theory for several individual characteristics and outcomes, and relating the two sets of measurements to each other. We show that personality traits have a comparable or stronger predictive power than do economic preferences for several dependent variables, including credit score, job persistence, and heavy truck accidents. They also have strong predictive power for Body Mass Index (BMI) and smoking status. Further, decision theory and personality variables are meaningfully related. For example, we confirm that cognitive ability explains a substantial part of time preferences, and find that Neuroticism and cognitive ability together explain attitudes toward risk. In addition, Agreeableness and cognitive ability explain aspects of other-regarding behavior in a strategic setting.

Efficiently locating conservation boundaries: Searching for the Tasmanian devil facial tumour disease front

Conservation management actions and decisions are often defined by the location of ecological boundaries, for example, the present range of invasive or threatened species. The position of these boundaries can be cryptic, and managers must therefore directly sample sites, an expensive and time-consuming process. While accurate boundary location techniques have been considered by ecological theorists, the issue of cost-effective, or optimal boundary location has not. We propose a general framework for boundary location which incorporates both cost-efficiency and uncertainty. To illustrate its application, we use it to help locate an infectious disease front in the endangered Tasmanian devil population. The method ensures optimal spatial sampling by maximizing the expected information gained from each sample. When resources are limited, our method provides more accurate estimates of the boundary location than traditional sampling protocols. Using a formal decision theory sampling design encourages economically efficient actions, and provides defensible and transparent rationale for management actions.

Optimal investment in conservation of species

Summary 1 Factors that have been considered when deciding how to invest resources in conservation of species include the efficacy and cost of management, the importance of the species, the level of threat, and the timeframe over which results are to be achieved. However, it is unclear how each of these different factors should be weighted and combined when making a decision. 2 We examine how the probabilities of species changing in IUCN Red List categories are influenced by expenditure of resources. We use these relationships to determine optimal investment strategies, using Australian birds as a case study. 3 The optimal level of investment in different species depends critically on whether managers wish to minimize the number of extinct species or a weighted average of all threatened species, and on the available budget. The level of investment should not necessarily reflect the level of threat. In our case study, the timeframe of management had little influence on the investment decision. 4 Our results show that extinctions of Australian birds can be largely avoided over the next 80 years given current expenditure, but greater investment in conservation is required to reduce the number of threatened species. 5 Synthesis and applications. The most efficient allocation of resources to conserve species is difficult to determine intuitively; therefore, this decision demands the use of formal decision theory. The influence of the particular management objective on the optimal decision means that this feature needs careful consideration. Our approach can be used to determine the level of investment that is required to reduce the number of threatened species.

Indicators of Usefulness of Test Scores

Current thinking on validity suggests that educational institutions and individuals should evaluate their uses of test scores in the context of their fundamental goals. Regression coefficients and other traditional criterion-related validity statistics provide relevant information, but often do not, by themselves, address the fundamental reasons for using test scores. Formal decision theory models provide a logically rigorous way to do this, but they are difficult to implement in practice. This article considers a simplification of formal decision theory models, in which one estimates the proportion of examinees for whom positive outcomes result from a use of test scores. For uses involving selection, the proportion of examinees with positive outcomes can be calculated by applying traditional regression coefficients to the marginal distribution of scores in the unselected population. The incremental usefulness of using a particular variable can be judged by comparing its proportion to that associated with no selection and to that associated with using another variable, either alone or jointly. Examples, related to college admission and retention, are given to illustrate these ideas.

The precautionary principle: a new approach to public decision-making?

The precautionary principle recommends preventing possible harm to human health and environment. It has gained support in the international community as a higher-order legal principle that should guide public policy and the formulation of specific laws. But it is also the target of much criticism, with many arguing that the principle is vacuous, inconsistent or based on an excessively conservative attitude towards risk. I argue that the value of the precautionary principle is that it emphasises aspects of good decision-making that go beyond the scope of formal decision theory, and are often neglected in practice. It is best conceived as providing guidelines for formulating a decision problem, as opposed to challenging standard decision rules. To this effect, the principle advocates assessment of acts relative to feasible alternatives, and proper representation of all potential outcomes of acts (including those outcomes that are probabilistic or scientifically uncertain). In terms of determining suitable outcome utilities and burdens of proof, I claim that the precautionary principle appeals to ethical ideals associated with ‘sustainable development’. I finally outline some general implications of the principle for environmental decision-making.

Machining Quality and Cost: Estimation and Tradeoffs

Simultaneous improvement of machining cost, quality and environmental impact is sometimes possible, but after the Pareto optimal frontier has been reached, decisions must be made regarding unavoidable tradeoffs. This paper presents a method for formulating a mathematical model for first estimating quality, cost and cutting fluid wastewater treatment impacts of two machining operations (end milling and drilling), and then for tradeoff decision making. The milling quality estimation model is developed through virtual experimentation on a simulation model, while the drilling quality estimation model is developed through physical experimentation. Cost is estimated through an activity based costing approach. Cutting fluid wastewater treatment impacts (BOD and TSS) are estimated through stoichiometric analysis of cutting fluids. Input decision variables include material choice, design, manufacturing and limited lubrication parameters. The contribution of this paper is the integration of activity based cost estimation, machining quality estimation via statistical analysis of data from virtual and physical experiments, cutting fluid wastewater treatment impact estimation and formal decision theory. A case study of an automotive steering knuckle is presented, where decision variables include material choice (cast iron versus aluminum), feed rate, cutting speed and wet versus dry machining.

Pešek lecture: SETI and society—decision trees

This paper presents a simplified decision tree diagram for SETI (the Search for Extraterrestrial Intelligence) and society. It deals with the series of steps and circumstances that follow from the quest for evidence of the existence of extraterrestrial civilizations, with the major goal of including those branch points which involve decisions that are societal rather than scientific or technological. Since SETI is based on science and technology these factors are also included in the decision diagram, but more in a summary fashion. A condensed list of the relevant societal disciplines is given. The most difficult decisions are those related to issues of transmitting communications from Earth to ETI. The diagram may be useful as a new way of looking at the subject of Communication with Extraterrestrial Intelligence (CETI), and how it inevitably blends into SETI. Arguments are made for vigorous pursuit of studies in all the societal, cultural and behavioral domains involved, and it is shown that many of these studies can profitably be undertaken now, before an ETI signal has been detected. Not least, it is argued that the newly emerging field of CETI and Society would benefit materially from the application of formal decision theory and analysis, and from game theory and utility theory.

Behavioral and Other Human Ecologies: Critique, Response and Progress through Criticism

This paper has three goals:()) to define the anthropological subfield of human behavioral ecology (HBE) and characterize recent progress in this research tradition; (2) to address Joseph's (2000) critique of HBE from the perspective of an advocate of that field; € and (3) to suggest features that make for effective criticism of research traditions. (1) HBE attempts to understand intra- and inter-societal diversity in human behavior as the product of species-wide adaptive goals which must be realized in highly diverse, socio-environmental circum- stances. Theoretically, HBE draws selectively from neo-Darwinism and its cultural-evolutionary analogs, from micro-economics, and from elements of formal decision and game theory. Applications generally use simple, formal models as heuristic devices for generating testable hypotheses about resource use, reproductive and social behavior, and life history traits. (2) Using Kuhn's (1977) and McMullin's (1983) criteria for assessing progress in a research tradition, I examine Joseph's review of HBE, indicating the several points on which we agree and the greater number for which I believe her criticisms are misplaced or in error. (3) Finally, I try to describe general features of effective critique, in the sense of critical commentary that enables the advance of scientific understanding through collective scholarly effort. Such criticism will be necessary if we are to sort out the relative strengths and potential contributions of the several research traditions in human ecology (e.g., cultural ecology, historical ecology, political ecology, etc.).

Issues in cognitive psychology: implications for professional education.

Experts clearly do not use classic formal decision theory, but rather make use of heuristics, or shortcuts, when making decisions. Nonetheless, experts generally make appropriate decisions. This suggests that the shortcuts are useful more often than not. Rather than teaching learners to avoid heuristics, then, it might be more reasonable to help them recognize those relatively infrequent situations where their heuristics are likely to fail.

Problem-based learning with database systems

Recent research has shown that students' academic performance depends not only on their own efforts but also on the total environment in which they study. To stimulate students' interest and encourage them to participate in the whole learning process, methods of problem-based learning (PBL) have been introduced in teaching database subjects in the School of Computer Science and Engineering at the University of New South Wales. This paper reports an experiment with PBL. In a database subject, students were first exposed to a practical problem in the form of a project and were asked to design and implement a database system to solve it. They were required to work in groups and to acquire other skills and knowledge not taught in the classroom. Formal decision theory was used in designing and obtaining the assessment criteria for evaluating the outcomes of PBL. The method invited students to participate in the evaluation process, creating a non-threatening environment for learning and providing a fair method of assessment. Their approaches to learning have been analysed using the Study Process Questionnaire (SPQ). The statistical results show that there is a significant linear relationship between students taking a deep or an achieving approach to learning and the outcomes of their projects.

On the Use of a Cumulative Distribution as a Utility Function in Educational or Employment Selection

Formal decision theory can make important contributions to educational or employment decision-making, provided one can quantify the utilities of different possible outcomes such as test scores and grade-point averages. Because utility is usually a monotonic increasing function of performance score, a cumulative probability function may be convenient for describing one’s utilities. Moreover, calculations of expected utility of a decision are greatly simplified when the utility and the probability function have the same functional form, e.g., both are normal. A least-squares procedure, developed by Lindley and Novick for fitting a utility function, is applied to truncated normal and extended beta distribution functions. The truncated normal and beta distributions avoid the symmetry and infinite range restrictions of the normal distribution and can provide fits in some cases in which the normal functional forms cannot provide a reasonable fit.