The robust beauty of majority rules in group decisions

How should groups make decisions? The authors provide an original evaluation of 9 group decision rules based on their adaptive success in a simulated test bed environment. When the adaptive success standard is applied, the majority and plurality rules fare quite well, performing at levels comparable to much more resource-demanding rules such as an individual judgment averaging rule. The plurality rule matches the computationally demanding Condorcet majority winner that is standard in evaluations of preferential choice. The authors also test the results from their theoretical analysis in a behavioral study of nominal human group decisions, and the essential findings are confirmed empirically. The conclusions of the present analysis support the popularity of majority and plurality rules in truth-seeking group decisions.     

On the power of multivariate latent growth curve models to detect correlated change

We evaluated the statistical power of single-indicator latent growth curve models (LGCMs) to detect correlated change between two variables (covariance of slopes) as a function of sample size, number of longitudinal measurement occasions, and reliability (measurement error variance). Power approximations following the method of Satorra and Saris (1985) were used to evaluate the power to detect slope covariances. Even with large samples (N = 500) and several longitudinal occasions (4 or 5), statistical power to detect covariance of slopes was moderate to low unless growth curve reliability at study onset was above .90. Studies using LGCMs may fail to detect slope correlations because of low power rather than a lack of relationship of change between variables. The present findings allow researchers to make more informed design decisions when planning a longitudinal study and aid in interpreting LGCM results regarding correlated interindividual differences in rates of development.     

Causal Attributions for Poorly Performing Projects: Their Effect on Project Continuation Decisions

This study examined the escalation problem within an attribution theory framework. Students read a case scenario containing causal attribution information that described a poorly performing project under their supervision. They made estimates of its future success, as well as a decision whether to continue it. Perceived stability of causality had the primary effect on expectancy of success. A project whose performance downturn was attributed to a stable cause had a lower expectancy. Locus of causality had a smaller but still significant effect. Project downturns attributed to internal causes had a lower expectancy. Expectancy of success was significantly correlated with project continuation decisions. Discrepancies between these results and those reported by Staw and Ross (1978) are accounted for in terms of Weiner's (1985, 1986) attributional analysis.     

Specifying optimum examinees for item parameter estimation in item response theory

Information functions are used to find the optimum ability levels and maximum contributions to information for estimating item parameters in three commonly used logistic item response models. For the three and two parameter logistic models, examinees who contribute maximally to the estimation of item difficulty contribute little to the estimation of item discrimination. This suggests that in applications that depend heavily upon the veracity of individual item parameter estimates (e.g. adaptive testing or text construction), better item calibration results may be obtained (for fixed sample sizes) from examinee calibration samples in which ability is widely dispersed.This work was supported by Contract No. N00014-83-C-0457, project designation NR 150-520, from Cognitive Science Program, Cognitive and Neural Sciences Division, Office of Naval Research and Educational Testing Service through the Program Research Planning Council. Reproduction in whole or in part is permitted for any purpose of the United States Government. The author wishes to acknowledge the invaluable assistance of Maxine B. Kingston in carrying out this study, and to thank Charles Lewis for his many insightful comments on earlier drafts of this paper.     

Adaptable Robots

In this essay we consider some of the characteristics of adaptive biological systems and how these might work as models in designing a robot intended for the exploration of complex environments. Trying to design a robot that has such properties forces one to think hard about the nature of those properties. Here we have one intersection between philosophy and computing. We consider the nature of adaptability and some properties of complex biological systems that are relevant to designing adaptive robots, including direct perception, animacy, affordances, redundant degress of freedom, collective decisions, and emergent properties. We explain how these concepts were used in the development of a robotic arm.     

A Comparison of Adaptive Behavior Ratings: Revised Vineland and AAMD ABS-SE

Although the assessment of adaptive behavior is a mandated component of many school assessments, concerns have been raised about the measurement of the construct and related professional practices. Estimates of adaptive behavior have been shown sometimes to vary by instruments and raters and therefore may influence placement decisions in unknown ways. This study examined the agreement among teachers and parents on the revised Vineland and the AAMD Adaptive Behavior Scale-School Edition for a sample of developmentally handicapped children. A sample of learning disabled children was also included in order to explore the effects of a restricted range on the correlations. Also, the potential effects of estimates of adaptive behavior on placement decisions were analyzed. The results suggest that serious discrepancies could occur that would directly affect placement decisions.     

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。     

A test of Weiner's attribution theory inertial motivation hypothesis1

This study (N= 160 males) examined the cognitive and inertial motivation effects of overt success feedback on subjects high and low in resultant achievement motivation. The cognitive effects of overt success feedback were investigated by requesting attributions to effort, ability, luck, and task difficulty concerning performance on a digit symbol substitution task. The inertial motivation effects of overt success feedback were investigated through a transfer design. Results indicated overt success feedback to have an inertial motivation effect on performance efficiency at a subsequent verbal learning task. The results provided evidence against Weiner's (1972) attribution theory version of the inertial motivation hypothesis, and were interpreted within the general learning theory framework combined with the achievement and test anxiety models of Atkinson and Sarason. The interpretation offered considers the various experimental conditions as sources of motivation.     

A low power fuzzy logic based variable resolution ADC for wireless ECG monitoring systems

Portable low power and high quality monitoring devices play an important role for improving the performance of wireless body sensor networks. Mixed signal processor is required in ECG monitoring unit that comprises of analog front end, analog to digital converter (ADC) and digital signal processor. ADC is a core element in mixed signal processing unit and the proper design of ADC is crucial for data acquisition without losing heart related information and originality. The adaptive sampling has been used in the existing ADCs for choosing the sampling clock adaptively. Adaptive sampling rate ADC performs compression and reduces power consumption to some extent, however low powers ADCs are essential in wireless healthcare monitoring systems. In this paper, fuzzy logic based variable resolution controller is proposed to design the ADC efficiently in terms of circuit complexity and power. To further reduce the power consumption, power gating technique is adopted for static power reduction. Under 90 nm CMOS technology, gate count, core area utilization and power consumption have been determined for existing adaptive sampling ADC and fuzzy logic based adaptive sampling ADC. Cadence design tools have been used for the measurement of power in the designed circuit. The performance has been found to be better in terms of area and power that are very much essential for wireless ECG monitoring systems.     

Cognitive models of choice: comparing decision field theory to the proportional difference model

People often face preferential decisions under risk. To further our understanding of the cognitive processes underlying these preferential choices, two prominent cognitive models, decision field theory (DFT; Busemeyer & Townsend, 1993 ) and the proportional difference model (PD; González-Vallejo, 2002 ), were rigorously tested against each other. In two consecutive experiments, the participants repeatedly had to choose between monetary gambles. The first experiment provided the reference to estimate the models' free parameters. From these estimations, new gamble pairs were generated for the second experiment such that the two models made maximally divergent predictions. In the first experiment, both models explained the data equally well. However, in the second generalization experiment, the participants' choices were much closer to the predictions of DFT. The results indicate that the stochastic process assumed by DFT, in which evidence in favor of or against each option accumulates over time, described people's choice behavior better than the trade-offs between proportional differences assumed by PD.     

The Role of Decision-Making Models and Reflection in Navigating Ethical Dilemmas

The ACA Code of Ethics (American Counseling Association [ACA], 2014) mandates counselor competency in using ethical decision-making models (EDMs) and mandates that counselors use an EDM when confronted with making ethical decisions. Additionally, researchers have highlighted the importance of counselors continually evaluating and reflecting when faced with ethical dilemmas and working through a decision-making model. Using a phenomenological research design, the authors examined how counselors address ethical dilemmas, including how reflection and EDMs are incorporated into the decision-making process. Emergent themes from data analysis include (a) incomplete following of EDMs, (b) varied dilemmas, (c) power, and (d) ethics training.     

Computational and performance aspects of PCA-based face-recognition algorithms

Algorithms based on principal component analysis (PCA) form the basis of numerous studies in the psychological and algorithmic face-recognition literature. PCA is a statistical technique and its incorporation into a face-recognition algorithm requires numerous design decisions. We explicitly state the design decisions by introducing a generic modular PCA-algorithm. This allows us to investigate these decisions, including those not documented in the literature. We experimented with different implementations of each module, and evaluated the different implementations using the September 1996 FERET evaluation protocol (the de facto standard for evaluating face-recognition algorithms). We experimented with (i) changing the illumination normalization procedure; (ii) studying effects on algorithm performance of compressing images with JPEG and wavelet compression algorithms; (iii) varying the number of eigenvectors in the representation; and (iv) changing the similarity measure in the classification process. We performed two experiments. In the first experiment, we obtained performance results on the standard September 1996 FERET large-gallery image sets. In the second experiment, we examined the variability in algorithm performance on different sets of facial images. The study was performed on 100 randomly generated image sets (galleries) of the same size. Our two most significant results are (i) changing the similarity measure produced the greatest change in performance, and (ii) that difference in performance of +/- 10% is needed to distinguish between algorithms.     

A tutorial on adaptive design optimization

Experimentation is ubiquitous in the field of psychology and fundamental to the advancement of its science, and one of the biggest challenges for researchers is designing experiments that can conclusively discriminate the theoretical hypotheses or models under investigation. The recognition of this challenge has led to the development of sophisticated statistical methods that aid in the design of experiments and that are within the reach of everyday experimental scientists. This tutorial paper introduces the reader to an implementable experimentation methodology, dubbed Adaptive Design Optimization, that can help scientists to conduct “smart” experiments that are maximally informative and highly efficient, which in turn should accelerate scientific discovery in psychology and beyond.     

Distorting the probability of treatment success to justify treatment decisions

This research examines the value-induced bias: do people justify medical decisions by distorting their perception of relevant probabilities? Subjects were given a “close-call” decision which involved weighing one week of treatment side effects with a low probability of treatment success against seven more weeks of having the disease symptoms. They were told a numeric probability estimate of treatment success for the population as a whole. Those subjects with the ability to justify getting (not getting) treatment inflated (reduced) their numeric probability judgment of treatment success relative to those without this ability. As in cognitive dissonance reduction, risk perceptions can be distorted to align beliefs with preferences. Distorted risk perceptions may lead to suboptimal medical decisions.     

Self-evaluation of abilities: accurate self-assessment versus biased self-enhancement

Past research indicates that individuals are keenly aware of the diagnostic implications of their performance. Theories differ, however, in regard to how this awareness influences task choice. According to the self-assessment view, individuals choose tasks that are maximally informative of abilities, regardless of self-esteem implications. According to the self-enhancement view, task choice is often mediated by a concern for self-esteem protection. In the first study, subjects chose among eight forms of a cognitive abilities test that varied in their diagnosticity of success, diagnosticity of failure, and difficulty. In accordance with the self-assessment view, test choice was found to be positively related to diagnosticity of success and, to a lesser extent, diagnosticity of failure. Test choice was also dependent on the interaction of diagnosticity and difficulty in a manner that was more consistent with the self-assessment view. In a second study that provided more precise measurement of perceived diagnosticity and expected success, results indicated that the motives for self-assessment and self-enhancement were each reliably related to task preference. Of the two, self-assessment motivation was a stronger determinant of task preference. Taken together, these results suggest that task choice is governed largely by a concern for accurate self-appraisal. Additional results, however, indicate that current models may require revisions that take into account the less-than-accurate appraisal of diagnosticity.     

On the locus of speed-accuracy trade-off in reaction time: inferences from the lateralized readiness potential

Lateralized readiness potentials (LRPs) were used to determine the stage(s) of reaction time (RT) responsible for speed-accuracy trade-offs (SATs). Speeded decisions based on several types of information were examined in 3 experiments, involving, respectively, a line discrimination task, lexical decisions, and an Erikson flanker task. Three levels of SAT were obtained in each experiment by adjusting response deadlines with an adaptive tracking algorithm. Speed stress affected the duration of RT stages both before and after the start of the LRP in all experiments. The latter effect cannot be explained by guessing strategies, by variations in response force, or as an indirect consequence of the pre-LRP effect. Contrary to most models, it suggests that SAT can occur at a late postdecisional stage.     

An Evolutionary Analysis of Learned Attention

Humans and many other species selectively attend to stimuli or stimulus dimensions—but why should an animal constrain information input in this way? To investigate the adaptive functions of attention, we used a genetic algorithm to evolve simple connectionist networks that had to make categorization decisions in a variety of environmental structures. The results of these simulations show that while learned attention is not universally adaptive, its benefit is not restricted to the reduction of input complexity in order to keep it within an organism's processing capacity limitations. Instead, being able to shift attention provides adaptive benefit by allowing faster learning with fewer errors in a range of ecologically plausible environments.     

Relationship of the WISC-R factors to the adaptive behavior scale-school edition in a referral sample

The Wechsler Intelligence Scale for Children-Revised (WISC-R) factor deviation quotients (DQ) were calculated for Verbal Comprehension (VCDQ), Perceptual Organization (PODQ), and Freedom From Distractibility (FDDQ) factors for 83 referred children aged 7 years, 5 months to 16 years, 2 months who received a psychoeducational evaluation. The DQs were then compared to the factor domain and Comparison scores of the Adaptive Behavior Scale-School Edition (ABS-SE) by separate stepwise regression analyses. The results indicated that the two significant models were Community Self-Sufficiency (F(3, 76)=6.67,p<.001,R²=.208) and the Comparison Score (F(3, 76)=7.30,p<.001, R²=.223). The VCDQ and Verbal IQ scores were essentially equal predictors of adaptive behavior, but the PODQ and Performance IQ scores were not predictive. It is suggested that practitioners using the ABS-SE consider the differential predictive characteristics of the Verbal IQ/VCDQ and Performance IQ/PODQ when making placement decisions and when predicting success in various programs. Verbal comprehension is presented as being a common construct that underlies the WISC-R and ABS-SE. The suggestion that cognitive processes enable persons to acquire skills that make performance of adaptive skills possible also is discussed.     

Enhanced avatar design using cognitive map-based simulation.

With the advent of the Internet era and the maturation of electronic commerce, strategic avatar design has become an important way of keeping up with market changes and customer tastes. In this study, we propose a new approach to an adaptive avatar design that uses cognitive map (CM) as a what-if simulation vehicle. The main virtue of the new design is its ability to change specific avatar design features with objective consideration of the subsequent effects upon other design features, thereby enhancing user satisfaction. Statistical analyses of focus group interview results with a group of experts majoring in avatars and CM showed that our proposed approach could be used to effectively analyze avatar design in an adaptive and practical manner when the market situation is changing.     

Comparison of basic assumptions embedded in learning models for experience-based decision making

The present study examined basic assumptions embedded in learning models for predicting behavior in decisions based on experience. In such decisions, the probabilities and payoffs are initially unknown and are learned from repeated choice with payoff feedback. We examined combinations of two rules for updating past experience with new payoff feedback and of two choice rule assumptions for mapping experience onto choices. The combination of these assumptions produced four classes of models that were systematically compared. Two methods were employed to evaluate the success of learning models for approximating players’ choices: One was based on estimating parameters from each person’s data to maximize the prediction of choices one step ahead, conditioned by the observed past history of feedback. The second was based on making a priori predictions for the entire sequence of choices using parameters estimated from a separate experiment. The results indicated the advantage of a class of models incorporating decay of previous experience, whereas the ranking of choice rules depended on the evaluation method used.