How forgetting aids heuristic inference

Some theorists, ranging from W. James (1890) to contemporary psychologists, have argued that forgetting is the key to proper functioning of memory. The authors elaborate on the notion of beneficial forgetting by proposing that loss of information aids inference heuristics that exploit mnemonic information. To this end, the authors bring together 2 research programs that take an ecological approach to studying cognition. Specifically, they implement fast and frugal heuristics within the ACT-R cognitive architecture. Simulations of the recognition heuristic, which relies on systematic failures of recognition to infer which of 2 objects scores higher on a criterion value, demonstrate that forgetting can boost accuracy by increasing the chances that only 1 object is recognized. Simulations of the fluency heuristic, which arrives at the same inference on the basis of the speed with which objects are recognized, indicate that forgetting aids the discrimination between the objects' recognition speeds.     

Heuristic and linear models of judgment: matching rules and environments

Much research has highlighted incoherent implications of judgmental heuristics, yet other findings have demonstrated high correspondence between predictions and outcomes. At the same time, judgment has been well modeled in the form of as if linear models. Accepting the probabilistic nature of the environment, the authors use statistical tools to model how the performance of heuristic rules varies as a function of environmental characteristics. They further characterize the human use of linear models by exploring effects of different levels of cognitive ability. They illustrate with both theoretical analyses and simulations. Results are linked to the empirical literature by a meta-analysis of lens model studies. Using the same tasks, the authors estimate the performance of both heuristics and humans where the latter are assumed to use linear models. Their results emphasize that judgmental accuracy depends on matching characteristics of rules and environments and highlight the trade-off between using linear models and heuristics. Whereas the former can be cognitively demanding, the latter are simple to implement. However, heuristics require knowledge to indicate when they should be used.     

Précis of Simple heuristics that make us smart

How can anyone be rational in a world where knowledge is limited, time is pressing, and deep thought is often an unattainable luxury? Traditional models of unbounded rationality and optimization in cognitive science, economics, and animal behavior have tended to view decision-makers as possessing supernatural powers of reason, limitless knowledge, and endless time. But understanding decisions in the real world requires a more psychologically plausible notion of bounded rationality. In Simple heuristics that make us smart (Gigerenzer et al. 1999), we explore fast and frugal heuristics--simple rules in the mind's adaptive toolbox for making decisions with realistic mental resources. These heuristics can enable both living organisms and artificial systems to make smart choices quickly and with a minimum of information by exploiting the way that information is structured in particular environments. In this précis, we show how simple building blocks that control information search, stop search, and make decisions can be put together to form classes of heuristics, including: ignorance-based and one-reason decision making for choice, elimination models for categorization, and satisficing heuristics for sequential search. These simple heuristics perform comparably to more complex algorithms, particularly when generalizing to new data--that is, simplicity leads to robustness. We present evidence regarding when people use simple heuristics and describe the challenges to be addressed by this research program.     

A Cognitive Anatomy of Political Trust and Respective Bases: Evidence from a Two‐City Survey in China

Building on contemporary research on social cognition and psychology, trust, political representation and accountability, and candidate evaluation, this article proposes to decompose political trust into two cognitively distinct but related components for examination: competence versus intention evaluations. This article further argues that people's evaluations of their government's competence and intention in governance can have distinct bases due to the varying accessibility of pertinent information. Using valid instruments from a unique sampling survey in two Chinese cities in 2005, this article tests the validity of this cognitive scheme. Empirical evidence shows that (1) the surveyed Chinese urban residents effectively differentiated between their central government's competence and intention in governance: on average, they had a quite positive assessment of the central government's intention to serve its people, despite their relatively pessimistic views of its competence to deliver good governance; (2) the Chinese urbanites did consult different sources of information and heuristics when evaluating their central government's competence and intention, respectively.     

认知闭合需要研究评述

认知闭合需要是个体稳定的认知特征,描述了个体在面对模糊情境时是否愿意系统处理信息的动机。已有研究表明,认知闭合需要对个体的信息处理过程和决策结果有显著的预测能力。总体上说,高认知闭合需要的个体更容易利用启发式进行思考,因此此类个体更容易受到过度归因、首因效应等的影响。虽然大多数的研究表明认知闭合需要是个体稳定的认知特质,但也有研究者发现环境因素如噪音等可以在一定程度上、在短时期内改变个体的认知闭合需要的水平。因此,在相关研究中,认知闭合需要既可以通过量表测量,也可以通过在实验中改变环境噪音和时间压力等方法来操纵。已有的关于认知闭合需要的研究也有不足之处。首先,如何引导高认知闭合者克服匆忙做出决策的动机并采用分析式的方式处理信息和进行决策,目前的相关研究还很少;其次,已有的关于认知闭合的研究大都为实验室研究,因此这些研究的外部效度较低;第三,认知闭合需要在冲突研究领域的应用被忽略了。未来有必要针对这些不足之处进行相应研究     

Rational Thought And Rational Behavior: A Review Of Bounded Rationality: The Adaptive Toolbox.

Standard economic theory says that the rational approach to a decision is to weigh all alternatives on all relevant dimensions and then to select the one with the highest weight. Such a procedure would maximize subjective expected utility. But, because of constraints on time and available information, people and other animals often bypass this process by using “fast and frugal” heuristics to make decisions. Rationality is thus said to be “bounded” by time and information constraints. The articles in this book describe and organize common heuristics. They show that use of such heuristics is generally the best approach to many real world problems and therefore not irrational. Heuristics evolved, they say, not as deviations from rationality but as aids to rationality in cases where the standard model would have proved to be too slow or inefficient. Although the approach of almost all of the authors of these papers is that of cognitive psychology—a focus on internal cognitive mechanisms—their findings and even their theories may be interpreted in terms of reinforcement and punishment acting on behavioral patterns.     

Information search activity: An overview

IntroductionThis article exposes a brief history of information search models, from general and behavioural models to cognitive ones and presents recent theoretical advances in this research field.Literature findingsSince the beginning of 1990s, many theoretical models have tried to describe and predict the human behaviours involved in the information search tasks, and specifically when this activity is performed in computer systems. Some of these models elaborated by psychologists have attempted to infer the cognitive processes involved.DiscussionInformation search can be considered as a complex cognitive activity that involves various individual (cognitive, affective), contextual and social factors.ConclusionWe also suggest research issues to be developed in order to increase our knowledge in this area and we plead for further research on specific concepts depending on future and/or recent areas of interest.     

A comparison of information processing and dynamical systems perspectives on problem solving

Abstract

This article compares the information processing and dynamical systems perspectives on problem solving. Key theoretical constructs of the information-processing perspective include “searching” a “problem space” by using “heuristics” that produce “incremental” changes such as reaching a “subgoal” to solve a puzzle. Key theoretical constructs of the dynamical-systems perspective include “positive attractors”, “negative attractors”, and “latent attractors” that can cause large “nonincremental” changes in the possibility of a solution through the “emergence” of new ideas and beliefs that can resolve a conflict. The proposed alignment maps dynamical-system constructs to information-processing constructs: state space to problem space, negative attractor to impasse, positive attractor to productive subgoal, latent attractor to implicit cognition, and nonincremental change to insight. The purpose of the mapping is to explore similarities and differences between these constructs. Research from cognitive and social psychology illustrates how using constructs from both perspectives is helpful. The concluding section on Future Directions recommends an agenda based on three objectives: (1) create ontologies to organise current knowledge, (2) conduct research to obtain new knowledge, and (3) provide education to inform students about this knowledge.     

研究人类使用启发式之五原则(英文)

快速节俭启发式框架假定人们使用一套简捷的决策策略——启发式——进行推理、选择、评价及其他决策。这些启发式策略能顺应任务情境结构中的规律, 利用人类的基本认知能力。正基于此, 启发式成就了适应性行为。本文拟对启发式框架进行回顾, 并简要陈述引导研究者研究人类适应性工具箱的五条原则。我们强调, 启发式模型应(ⅰ)精确界定(ⅱ)对照检验(ⅲ)与策略选择理论相符(ⅳ)能评估其对新资料的预测力(ⅴ)能既在实验室又在现实世界中得以检验。     

Heuristics made easy: an effort-reduction framework

In this article, the authors propose a new framework for understanding and studying heuristics. The authors posit that heuristics primarily serve the purpose of reducing the effort associated with a task. As such, the authors propose that heuristics can be classified according to a small set of effort-reduction principles. The authors use this framework to build upon current models of heuristics, examine existing heuristics in terms of effort-reduction, and outline how current research methods can be used to extend this effort-reduction framework. This framework reduces the redundancy in the field and helps to explicate the domain-general principles underlying heuristics.     

The Limitations of Heuristics for Political Elites

Despite the extensive literature on citizens' use of cognitive heuristics in political settings, far less is known about how political elites use these shortcuts. Legislative elites benefit from the efficiency of the accessibility heuristic, but their judgments can also be flawed if accessible information is incomplete or unrepresentative. Using personal interviews and a quasi-experimental design, this paper examines the use of the accessibility heuristic by professional legislative staff when assessing the importance of natural resources issues to their constituents. Staff members recall only a small subset of the relevant constituents in the district, and this subset is biased in favor of active and resource-rich constituents over other, equally relevant constituents. This paper provides a new application of cognitive psychology to political elites and addresses important normative questions about the importance of information processing for political representation. By drawing on the psychology literature on heuristics, this paper identifies the cognitive mechanisms of congressional representation and provides new evidence of old biases.     

认知神经科学的心理学理论价值

从认知神经科学面临的三个挑战--(1)神经科学是“还原” 的,不能完全解释一个人的心理活动过程;（2）认知神经科学无法真正解释人的心理与行为;（3）认知神经科学只能揭示出神经事件与认知活动或行为活动的相关性--入手来讨论其心理学理论价值,阐明认知神经科学在心理学研究中的重要地位及主流趋势。同时指出,认知神经科学只是心理学学科门类中的一种,它能解决的问题也只限于特定的范围,对它要有科学理性的认识和定位。     

认知闭合需要、框架效应与决策偏好

在带有模糊性的决策情境中,决策者个人的认知特征会对其判断决策产生重要影响。通过实验的方法,考察了认知闭合需要和特征框架效应对个体决策偏好的影响。93名工商管理硕士（MBA）参与了实验,研究的结果支持了本研究的3个假设,即认知闭合需要与特征框架效应不仅对被试的决策偏好存在显著的影响,而且二者还存在显著的交互作用。具体来说,研究发现,在模糊情境中：高认知闭合需要的被试偏好于立刻做出决策,而低认知闭合需要的被试偏好于暂缓做出决策;接收到正向框架信息的被试偏好于立刻做出决策,而接收到负向框架信息的被试偏好于暂缓做出决策;认知闭合需要与特征框架对被试的决策偏好还存在显著的交互作用。研究结论为根据个体认知闭合需要的水平来选拔决策者、利用框架效应来影响个体的信息加工方式进而提高决策质量提供了理论依据     

How (far) can rationality be naturalized?

The paper shows why and how an empirical study of fast-and-frugal heuristics can provide norms of good reasoning, and thus how (and how far) rationality can be naturalized. We explain the heuristics that humans often rely on in solving problems, for example, choosing investment strategies or apartments, placing bets in sports, or making library searches. We then show that heuristics can lead to judgments that are as accurate as or even more accurate than strategies that use more information and computation, including optimization methods. A standard way to defend the use of heuristics is by reference to accuracy-effort trade-offs. We take a different route, emphasizing ecological rationality (the relationship between cognitive heuristics and environment), and argue that in uncertain environments, more information and computation are not always better (the ??less-can-be-more?? doctrine). The resulting naturalism about rationality is thus normative because it not only describes what heuristics people use, but also in which specific environments one should rely on a heuristic in order to make better inferences. While we desist from claiming that the scope of ecological rationality is unlimited, we think it is of wide practical use.     

Visions of rationality

The classical view that equates rationality with adherence to the laws of probability theory and logic has driven much research on inference. Recently, an increasing number of researchers have begun to espouse a view of rationality that takes account of organisms' adaptive goals, natural environments, and cognitive constraints. We argue that inference is carried out using boundedly rational heuristics, that is, heuristics that allow organisms to reach their goals under conditions of limited time, information, and computational capacity. These heuristics are ecologically rational in that they exploit aspects of both the physical and social environment in order to make adaptive inferences. We review recent work exploring this multifaceted conception of rationality.     

The Influence of Spokesperson Trustworthiness on Message Elaboration,Attitude Strength,and Advertising Effectiveness

Recent research has shown that information presented by untrustworthy endorsers is likely to be thoughtfully elaborated, whereas information presented by trustworthy endorsers is likely to be unthinkingly accepted (Priester & Petty, 1995). Study 1 manipulated argument quality and assessed cognitive responses to demonstrate that this influence of trustworthiness on persuasion holds for familiar endorsers likely to be used in actual advertisements. Study 2 demonstrated that trustworthiness can be influenced by individuals endorsing too many products, with similar persuasion consequences (i.e., untrustworthy endorsers prompt greater scrutiny of product‐related attributes than trustworthy endorsers). Study 2 also found that the attitudes that resulted from an untrustworthy endorser came to mind faster, even when those attitudes were equivalently positive—thus demonstrating that elaboration can influence attitude accessibility. This research provides evidence that attitude extremity may not be a sufficient indicator of advertising effectiveness, in that equally extreme attitudes can vary as to the bases by which they were formed, their underlying strength, and their effectiveness. Further, this research provides theoretical and strategic insight into the use of trustworthy and untrustworthy endorsers.     

Rules all the way down: Consumer behaviour from the standpoint of the ‘ONE behavioural’ research programme

This article sets out a unified behavioural research programme that integrates compatible elements of old, new and evolutionary behavioural approaches to economics as an alternative to the dominant unified approach to economics based on rational choice theory and a Walrasian view of market coordination. However, the proposed programme can also be viewed as a general framework for interdisciplinary research on consumer behaviour. It employs the view of scientific research programmes proposed by Lakatos, setting out groups of ‘hard-core’ propositions and their associated ‘do’ and ‘do not’ rules for the conduct of researchers. The unifying theme is that evolution in the economy (and in human systems more generally) entails the creation, adoption and abandonment of rules for dealing effectively with open-ended choice problems that are bedevilled by infinite regress problems and cognitive challenges that people seek to address via personal repertoires of hierarchically related rules. To anticipate behaviour, researchers need to develop knowledge of these rules (including heuristics and routines), their functionality and the processes by which they get changed or prove difficult to change even where they cause problems.     

Ignorance or integration: the cognitive processes underlying choice behavior

The fast‐and‐frugal heuristic framework assumes noncompensatory tools for human preferences (i.e., priority heuristic) and inferences (i.e., take the best heuristic). According to this framework, these heuristics predict choice behavior as well as model the cognitive processes underlying such behavior. The current paper presents two studies that juxtapose predictions derived from these two simple heuristics with alternative predictions derived from compensatory principles. Dependent measures that included reaction time, choice pattern, confidence level, and accuracy were better predicted by compensatory indices than by noncompensatory indices. These findings suggest that people do not rely on limited arguments only, but tend to integrate all acquired information into their choice processes. This tendency was replicated even when the experimental task facilitated the use of noncompensatory principles. We argue that the fast and frugal heuristics can predict the final outcome only under certain conditions, but even in these particular situations they are not applicable to the processes underlying choice behavior. An integrative model for choice behavior is proposed that better represents the data. Copyright © 2009 John Wiley & Sons, Ltd.     

The Nature of External Representations in Problem Solving

This article proposes a theoretical framework for external representation based problem solving. The Tic-Tac-Toe and its isomorphs are used to illustrate the procedures of the framework as a methodology and test the predictions of the framework as a functional model. Experimental results show that the behavior in the Tic-Tac-Toe is determined by the directly available information in external and internal representations in terms of perceptual and cognitive biases, regardless of whether the biases are consistent with, inconsistent with, or irrelevant to the task. It is shown that external representations are not merely inputs and stimuli to the internal mind and that they have much more important functions than mere memory aids. A representational determinism is suggested—the form of a representation determines what information can be perceived, what processes can be activated, and what structures can be discovered from the specific representation.