Ambiguity and rationality

Recently, several theories of decision making and probability judgment have been proposed that take into account ambiguity (Einhorn and Hogarth, 1985; Gardenfors and Sahlin, 1982). However, none of these theories explains exactly what the psychological causes of ambiguity are or addresses the issue of whether ambiguity effects are rational. In this paper, we define ambiguity as the subjective experience of missing information relevant to a prediction. We show how this definition can explain why ambiguity affects decisions in the ways it does. We argue that there are a variety of rational reasons ambiguity affects probability judgments and choices in the ways it does. However, we argue that the ambiguity effect does not cast doubt on the claim that utility theory is a standard of rational choice. Rather, we suggest that the effect of ambiguity on decisions highlights the fact that utility theory, like any normative model of decision making only prescribes the optimal decision, given what one knows.     

Decision rules in the perception and categorization of multidimensional stimuli

This article examines decision processes in the perception and categorization of stimuli constructed from one or more components. First, a general perceptual theory is used to formally characterize large classes of existing decision models according to the type of decision boundary they predict in a multidimensional perceptual space. A new experimental paradigm is developed that makes it possible to accurately estimate a subject's decision boundary in a categorization task. Three experiments using this paradigm are reported. Three conclusions stand out: (a) Subjects adopted deterministic decision rules, that is, for a given location in the perceptual space, most subjects always gave the same response; (b) subjects used decision rules that were nearly optimal; and (c) the only constraint on the type of decision bound that subjects used was the amount of cognitive capacity it required to implement. Subjects were not constrained to make independent decisions on each component or to attend to the distance to each prototype.     

Information about expert decision and post‐decision distortion of facts of own decision

Cognitive representations of decision problems are dynamic. During and after a decision, evaluations and representations of facts change to support the decision made by a decision maker her‐ or himself (Svenson, 2003). We investigated post‐decision distortion of facts (consolidation). Participants were given vignettes with facts about two terminally ill patients, only one of whom could be given lifesaving surgery. In Study 1, contrary to the prediction, the results showed that facts were distorted after a decision both by participants who were responsible for the decisions themselves and when doctors had made the decision. In Study 2 we investigated the influence of knowledge about expert decisions on a participant's own decision and post‐decisional distortion of facts. Facts were significantly more distorted when the participant's decision agreed with an expert's decision than when the participant and expert decisions disagreed. The findings imply that knowledge about experts' decisions can distort memories of facts and therefore may obstruct rational analyses of earlier decisions. This is particularly important when a decision made by a person, who is assumed to be an expert, makes a decision that is biased or wrong.     

迫选规则体验法: 检验规范性和描述性风险决策理论的新尝试

为寻求检验规范性和描述性风险决策理论的通用标准, 本研究以期望价值理论和齐当别抉择模型为例, 探讨了“迫选规则体验法”的适用性。被试为120名大学生, 实验任务为要求被试分别完成自主决策(采用未知规则: 真规则)和规则迫选决策(遵循给定规则: 假规则)任务, 并对决策后的情感和认可程度进行评定。研究发现: (1) 被试在自主决策条件下比在规则迫选条件下体验到的正性情感程度更强, 负性情感的程度更弱; (2) 被试在自主决策与规则迫选决策两种条件下做出的相同决策越多, 该被试对迫选规则更加认可并体验到的正性情感程度越强, 负性情感的程度越弱; (3) 与期望价值理论相比, 齐当别抉择模型可能符合更多决策者的实际决策规则。这些结果表明, 作为检验规范性和描述性风险决策理论的新尝试, 迫选规则体验法可能更有助于回答“决策者实际采用的决策规则是什么”的问题。     

Gandalf’s solution to the Newcomb problem

This article proposes a new theory of rational decision, distinct from both causal decision theory (CDT) and evidential decision theory (EDT). First, some intuitive counterexamples to CDT and EDT are presented. Then the motivation for the new theory is given: the correct theory of rational decision will resemble CDT in that it will not be sensitive to any comparisons of absolute levels of value across different states of nature, but only to comparisons of the differences in value between the available options within states of nature; however, the correct theory will also resemble EDT in that it will rely on conditional probabilities (not unconditional probabilities). The new theory gives a prominent role to the notion of a “benchmark” for each state of nature, by comparison with which the value of the available options in that state of nature are measured, and so it has been called the Benchmark Theory (BT). It is argued that BT gives the right verdict on the cases that seem to be counterexamples to CDT and EDT. Finally, some objections to BT are considered and answered.     

Foundations of Everyday Practical Reasoning

“Since today is Saturday, the grocery store is open today and will be closed tomorrow; so let’s go today”. That is an example of everyday practical reasoning—reasoning directly with the propositions that one believes but may not be fully certain of. Everyday practical reasoning is one of our most familiar kinds of decisions but, unfortunately, some foundational questions about it are largely ignored in the standard decision theory: (Q1) What are the decision rules in everyday practical reasoning that connect qualitative belief and desire to preference over acts? (Q2) What sort of logic should govern qualitative beliefs in everyday practical reasoning, and to what extent is that logic necessary for the purposes of qualitative decisions? (Q3) What kinds of qualitative decisions are always representable as results of everyday practical reasoning? (Q4) Under what circumstances do the results of everyday practical reasoning agree with the Bayesian ideal of expected utility maximization? This paper proposes a rigorous decision theory for answering all of those questions, which is developed in parallel to Savage’s (1954) foundation of expected utility maximization. In light of a new representation result, everyday practical reasoning provides a sound and complete method for a very wide class of qualitative decisions; and, to that end, qualitative beliefs must be allowed to be closed under classical logic plus a well-known nonmonotonic logic—the so-called system ?.     

行为决策理论在能源节约管理中的应用

能源短缺是人类面临的重要课题,节约能源是人类需要采取的刻不容缓的行动。仅仅依赖金钱刺激很难解决能源浪费问题,而心理与行为科学可以发挥重要作用。本文梳理了应用行为决策的经典理论(如,安于现状偏差、决策双系统模型、参照点效应、框架效应和社会规范等)促进节能行为的研究成果,同时总结了诸如情绪、认知对象特点、信息呈现等影响个体节能行为的因素,最后从开展本土化研究、研究方式改进和拓展应对措施的角度对未来研究提出建议。希望本文能给心理学研究者一定的借鉴和启发,在节能管理领域做出更有价值的研究,以最终提高民众节能意识、增加民众节能行为。     

The Relevance of Decision Theory to Ethical Theory

Morality for the purposes of this paper consists of sets of rules or principles intended for the general regulation of conduct for all. Intuitionist accounts of morality are rejected as making reasoned analysis of morals impossible. In many interactions, there is partial conflict and partial cooperation. From the general social point of view, the rational thing to propose is that we steer clear of conflict and promote cooperation. This is what it is rational to propose to reinforce, and to assist in reinforcing in society; it is not necessarily what it is individually rational to do. Even so, given the general situation, the rationality of its reinforcement will typically support the rationality of individual action as well. Game theory makes it possible to clarify these interactions, and these proposals for social solutions.     

Bayesian probability

Bayesian decision theory is here construed as explicating a particular concept of rational choice and Bayesian probability is taken to be the concept of probability used in that theory. Bayesian probability is usually identified with the agent’s degrees of belief but that interpretation makes Bayesian decision theory a poor explication of the relevant concept of rational choice. A satisfactory conception of Bayesian decision theory is obtained by taking Bayesian probability to be an explicatum for inductive probability given the agent’s evidence.     

Approval-directed agency and the decision theory of Newcomb-like problems

Decision theorists disagree about how instrumentally rational agents, i.e., agents trying to achieve some goal, should behave in so-called Newcomb-like problems, with the main contenders being causal and evidential decision theory. Since the main goal of artificial intelligence research is to create machines that make instrumentally rational decisions, the disagreement pertains to this field. In addition to the more philosophical question of what the right decision theory is, the goal of AI poses the question of how to implement any given decision theory in an AI. For example, how would one go about building an AI whose behavior matches evidential decision theory’s recommendations? Conversely, we can ask which decision theories (if any) describe the behavior of any existing AI design. In this paper, we study what decision theory an approval-directed agent, i.e., an agent whose goal it is to maximize the score it receives from an overseer, implements. If we assume that the overseer rewards the agent based on the expected value of some von Neumann–Morgenstern utility function, then such an approval-directed agent is guided by two decision theories: the one used by the agent to decide which action to choose in order to maximize the reward and the one used by the overseer to compute the expected utility of a chosen action. We show which of these two decision theories describes the agent’s behavior in which situations.

     

"Leaky" Rationality: How Research on Behavioral Decision Making Challenges Normative Standards of Rationality

ABSTRACT— For more than 30 years, decision-making research has documented that people often violate various principles of rationality, some of which are so fundamental that theorists of rationality rarely bother to state them. We take these characteristics of decision making as a given but argue that it is problematic to conclude that they typically represent departures from rationality. The very psychological processes that lead to "irrational" decisions (e.g., framing, mental accounting) continue to exert their influence when one experiences the results of the decisions. That is, psychological processes that affect decisions may be said also to "leak" into one's experience. The implication is that formal principles of rationality do not provide a good enough normative standard against which to assess decision making. Instead, what is needed is a substantive theory of rationality—one that takes subjective experience seriously, considers both direct and indirect consequences of particular decisions, considers how particular decisions fit into life as a whole, and considers the effects of decisions on others. Formal principles may play a role as approximations of the substantive theory that can be used by theorists and decision makers in cases in which the formal principles can capture most of the relevant considerations and leakage into experience is negligible.     

Multiattribute Decision Making in Context: A Dynamic Neural Network Methodology

A theoretical structure for multiattribute decision making is presented, based on a dynamical system for interactions in a neural network incorporating affective and rational variables. This enables modeling of problems that elude two prevailing economic decision theories: subjective expected utility theory and prospect theory. The network is unlike some that fit economic data by choosing optimal weights or coefficients within a predetermined mathematical framework. Rather, the framework itself is based on principles used elsewhere to model many other cognitive and behavioral data, in a manner approximating how humans perform behavioral functions. Different, interconnected modules within the network encode (a) attributes of objects among which choices are made, (b) object categories, (c) and goals of the decision maker. An example is utilized to simulate the actual consumer choice between old and new versions of Coca-Cola. Potential applications are also discussed to market decisions involving negotiations between participants, such as international petroleum traders.     

The belief-bias effect in formal reasoning: The influence of knowledge on logic

The present study examines the applicability of a rational model of categorical inference (e.g., Revlis, 1975b) to account for the apparently irrational decisions students reach on categorical syllogisms. In Experiment 1, students judged the logical validity of emotionally neutral conclusions to controversial premises. Of the reasoners’ decisions, 80% can be accounted for by the application of rational rules to their idiosyncratic encoding of the syllogistic premises. In Experiment 2, students were asked to solve syllogisms whose conclusions varied in truth value. When asked to reason about controversial, if not emotional, material, students do not suspend rational choice, but rather, their decisions are judicious ones, flowing logically from their idiosyncratic understanding of the materials reasoned about. When errors do occur, they result from an interrupt to rational processes and reflect conflict between competing goals rather than a switch to irrational decision processes.     

The rationality of conditional cooperation

InMorals by Agreement, David Gauthier (1986) argues that it is rational to intend to cooperate, even in single-play Prisoner's Dilemma games, provided (1) your co-player has a similar intention; (2) both intentions can be revealed to the other player. To this thesis four objections are made. (a) In a strategic decision the parameters on which the argument relies cannot be supposed to be given. (b) Of each pair ofa-symmetric intentions at least one is not rational. But it is impossible to form symmetric intentions to cooperate conditionally. For the condition on which the decision depends cannot be fulfilled without deciding. (c) If one's intention has to be ascertained on the basis of information about one's past performance, it is straightforwardly rational to intend to cooperate, but there is no reason to do so in a single-play PD. (d) The argument cannot be extended ton-person games which are Gauthier's principal concern.     

Overcoming focusing failures in competitive environments

This paper attacks one of the chief limitations of the field of behavioral decision research—the past inability to use this literature to improve decision making. Building on the work of Thompson, Gentner, Loewenstein and colleagues (Loewenstein, Thompson, & Gentner, 1999; Thompson, Gentner, & Loewenstein, 2000; Gentner & Markman, 1997), the current paper finds that it is possible to reduce bias in one of the most robust problems in the decision literature, the Acquiring a Company Problem (Samuelson & Bazerman, 1985). Past research has shown that individuals make suboptimal offers as a result of the failure to think about the decisions of others and to incorporate a clear understanding of the rules of the game. In the current study, we find that by allowing study participants to see and understand differences in seemingly unrelated decision problems—versions of the Monty Hall Game (Nalebuff, 1987; Friedman, 1998) and Multiparty Ultimatum Game (Messick, Moore, & Bazerman, 1997; Tor & Bazerman, 2003)—study participants can learn to focus more accurately on the decisions of other parties and the rules of the game, the keys to solving the Acquiring a Company Problem. This research offers a new piece of evidence that comparative and analogical processes may be a successful direction for improving decision making. Copyright © 2004 John Wiley & Sons, Ltd.     

Dynamical evolutionary psychology: individual decision rules and emergent social norms

A new theory integrating evolutionary and dynamical approaches is proposed. Following evolutionary models, psychological mechanisms are conceived as conditional decision rules designed to address fundamental problems confronted by human ancestors, with qualitatively different decision rules serving different problem domains and individual differences in decision rules as a function of adaptive and random variation. Following dynamical models, decision mechanisms within individuals are assumed to unfold in dynamic interplay with decision mechanisms of others in social networks. Decision mechanisms in different domains have different dynamic outcomes and lead to different sociospatial geometries. Three series of simulations examining trade-offs in cooperation and mating decisions illustratehow individual decision mechanisms and group dynamics mutually constrain one another, and offer insights about gene-culture interactions.     

Choosing an inferior alternative

We show how decision makers can be induced to choose a personally inferior alternative, a strong violation of rational decision making. First, the inferior alternative is installed as the leading option by starting with information that supports this alternative. Then, the decision maker uses the natural process of distorting new information to support whichever alternative is leading. This leader-supporting distortion overcomes the inherent advantages of the superior alternative. The end result is a tendency to choose the self-identified inferior alternative. We trace the choice process to reveal the amount of distortion and its influence on preference. Self-reported awareness of distortion to support the inferior alternative is not related to the amount of distortion. The absence of valid awareness suggests that the manipulation that produces this preference violation is unlikely to be detected and that the distortion is unlikely to be corrected by the decision maker. As expected, given the lack of awareness, final confidence is just as high when the inferior alternative is chosen as when the superior one is. The discussion considers how to prevent an adversary from manipulating one's decisions using this technique.     

Sex and race discrimination resulting from manager-client relationships: Applying the rational bias theory of managerial discrimination

Rational bias theory predicts that discrimination may be situationally influenced by circumstances in which a show of bias seems likely to be rewarded or punished by others. This study applies the theory in an examination of managerial sex and race discrimination in situations in which normative or unusual signals are given. In agreement with rational bias theory, the participants, acting in the role of managers, indicated that they would be less likely to discriminate in personnnel decisions with cues indicating that discrimination might not be needed or wanted. The results are interpreted as supportive of rational bias theory and as useful for the design of new policies aimed at ending discrimination. The findings also suggest that the importance of discrimination against blacks of both sexes in management has been widely ignored.     

A multidimensional framework for financial–economic decisions

Most financial–economic decisions are made consciously, with a clear and constant drive to ‘good’, ‘better’ or even ‘optimal’ decisions. Nevertheless, many decisions in practice do not earn these qualifications, despite the availability of financial economic theory, decision sciences and ample resources. We plea for the development of a multidimensional framework to support financial economic decision processes. Our aim is to achieve a better integration of available theory and decision technologies. We sketch (a) what the framework should look like, (b) what elements of the framework already exist and which not, and (c) how the MCDA community can co‐operate in its development. Copyright © 2003 John Wiley & Sons, Ltd.