Positive reinforcement and the elimination of reinforced responses

Key pecking was maintained on a fixed-interval schedule while either a differential-reinforcement-of-not-responding or a fixed-time schedule was imposed simultaneously. The lower the time parameter of the not-responding schedule, the lower was the response rate. Similar effects occurred with the fixed-time schedule, if the pigeons had experience with reinforcement for not responding. Otherwise the effects were less orderly, to the extent that rate could reach maximum with the lowest-valued fixed-time schedule. The not-responding and the response-independent schedules had similar effects on rate in experienced pigeons only when the time parameter or nominal frequency of food presentation was considered. When considered in terms of obtained frequency of food presentation, reinforcement of not responding produced larger decrements in rate than did the fixed-time schedule.     

Stimulus control of differential-reinforcement-of-low-rate responding

Five pigeons were given single-stimulus training on an 8-sec differential-reinforcement-of-low-rate schedule followed by steady-state generalization training using 12 wavelength stimuli. Three birds had a high percentage of reinforced responses on the training schedule and flat generalization gradients of total responses. The birds with fewer reinforced responses had much steeper generalization gradients. Generalization gradients plotted as a function of both stimulus wavelength and interresponse time showed that for most birds, stimulus control was restricted to responses with long interresponse times. Responses with very short interresponse times were not under stimulus control and there was some evidence of inhibitory control of short interresponse times. Interresponse-times-per-opportunity functions, plotted as a function of stimulus wavelength, showed that stimulus wavelength controlled the temporal distribution of responses, rather than the overall rate of response. The data indicate that the differential-reinforcement-of-low-rate schedule generates several response categories that are controlled in different ways by wavelength and time-correlated stimuli, and that averaging responses regardless of interresponse-time length obscures this control.     

Alternative response training, differential reinforcement of other behavior, and extinction in squirrel monkeys (Saimiri sciureus)

In Experiment I, (a) extinction, (b) extinction plus reinforcement of a discrete alternative response, and (c) differential reinforcement of other behavior were each correlated with a different stimulus in a three-component multiple schedule. The alternative-response procedure more rapidly and completely suppressed behavior than did differential reinforcement of other behavior. Differential reinforcement of other behavior was slightly more effective than extinction alone. In Experiment II, reinforcement of specific alternative behavior during extinction and differential reinforcement of other behavior were used in two components, while one component continued to provide reinforcement for the original response. Once again, the alternative-response procedure was most effective in reducing responding as long as it remained in effect. However, the responding partially recovered when reinforcement for competing behavior was discontinued. In general, responding was less readily reduced by differential reinforcement of other behavior than by the specific alternative-response procedure.     

A note on computing Louis’ observed information matrix identity for IRT and cognitive diagnostic models

Using Louis’ formula, it is possible to obtain the observed information matrix and the corresponding large-sample standard error estimates after the expectation–maximization (EM) algorithm has converged. However, Louis’ formula is commonly de-emphasized due to its relatively complex integration representation, particularly when studying latent variable models. This paper provides a holistic overview that demonstrates how Louis’ formula can be applied efficiently to item response theory (IRT) models and other popular latent variable models, such as cognitive diagnostic models (CDMs). After presenting the algebraic components required for Louis’ formula, two real data analyses, with accompanying numerical illustrations, are presented. Next, a Monte Carlo simulation is presented to compare the computational efficiency of Louis’ formula with previously existing methods. Results from these presentations suggest that Louis’ formula should be adopted as a standard method when computing the observed information matrix for IRT models and CDMs fitted with the EM algorithm due to its computational efficiency and flexibility.     

Modeling Asymmetry in the Time–Distance Relation of Ordinal Personality Items

In analyzing responses and response times to personality questionnaire items, models have been proposed which include the so-called “inverted-U effect.” These models predict that response times to personality test items decrease as the latent trait value of a given person gets closer to the attractiveness of an item. Initial studies into these models have focused on dichotomous personality items, and more recently, models for Likert-type scale items have been proposed. In all these models, it is assumed that the inverted-U effect is symmetrical around 0, while, as will be explained in this article, there are substantive and statistical reasons to study this assumption. Therefore, in this article, a general inverted-U model is proposed which accommodates two sources of asymmetry between the response times and the attractiveness of the items. The viability of this model is demonstrated in a simulation study, and the model is applied to the responses and response times of the Temperament and Character Inventory–Revised, covering a broad range of personality dimensions.     

Do early birds share their worms? How prosocial behaviour and empathy vary across the day

Social behaviours have been proposed to follow circadian patterns across the course of the day, but empirical support is mixed. As a within-subject test of circadian effects on everyday behaviour, we conduct an experience-sampling study with a near-representative population of 285 Americans (7405 observations). Prosocial behaviour and empathy were both somewhat more frequent in the morning (d = 0.08). However, these non-linear patterns only described morning-type participants; evening-types had consistent (and lower) rates of prosocial behaviour and empathy across time-of-day. These patterns were explained by morning-types reporting more social opportunities earlier in the day. These findings suggest that small, within-subject diurnal effects on social behaviour occur in daily life, and that some circadian effects may be driven by situation selection.     

Quitters would not prosper: Examining the relationship between online assessment performance and assessment attrition behavior

Hiring managers are often hesitant to implement online assessments over concerns that higher‐quality candidates are more likely to quit lengthy assessment batteries than lower‐quality candidates. In this paper, we present the results of two studies that collectively challenge this assumption. In Study 1, data from 327,517 job‐seekers spanning eight hiring contexts showed that assessment performance was negatively associated with subsequent assessment attrition behavior. In Study 2, we replicated this pattern of effects in two additional samples comprising 1,844,604 applicants for hourly associate positions, and 18,937 applicants for nursing positions. Collectively, these findings suggest that some degree of attrition may ultimately benefit, rather than harm, organizations using prehire assessments.     

自发性知觉经络反应中产生刺麻感和积极情绪的原因

自发性知觉经络反应(autonomous sensory meridian response,ASMR)是指在特定的视听刺激下,某些个体(ASMR敏感个体)在头皮后部、颈部乃至全身体验到一种令人极度愉快和放松的刺麻感的现象。其中,刺麻感的产生可能是个体大脑中负责感觉和肌肉运动的脑区高度激活引起的; 而与情绪和奖赏有关脑区的高度激活以及心率和呼吸频率的下降可能是产生愉快和放松感的重要原因。相比普通个体,ASMR敏感个体具有较高的神经质、共情特质、感觉受暗示性和特质正念。这可能说明ASMR敏感个体的感觉敏感性较高,情绪稳定性较弱,且比较关注自己身体的内外感受。这些个性特质可能导致ASMR敏感个体对某些视听刺激中所包含的一些感觉和情绪信息更加敏感,对其反应也更加强烈。目前,ASMR已经被用于抑郁,压力,失眠和慢性疼痛等的临床治疗以及商业广告之中。但ASMR可能会干扰个体的执行功能,在认知控制需求较高的情景下应尽量避免接触ASMR刺激。     

Decision-making bioinspired model for target definition and “satisfactor” selection for physiological needs

Every person, from an early age, has to make decisions to resolve situations that arise in life. In general, different people make different decisions in the same situation, since decision-making takes into account different factors such as age, emotional state, experience, among others. We can make decisions about situations that we classify as: more important than others, routine, unexpected, or trivial. However, making the correct decision(s) in a timely manner for these situations is one of the most complex and delicate challenges that human beings face. This is due to the arduous mental process required to be carried out. Providing such behavior to a virtual entity is possible through the use of Cognitive Architectures (CAs). CAs are an approach for modeling human intelligence and behavior. This paper presents an functional bioinspired computational decision-making model to satisfy the physiological needs of hunger and thirst. Our proposal considers as black boxes other cognitive functions that are part of a general CA (named Cuäyöllötl or brain in Nahuatl). In the proposed case study, it is proved that the decision-making process plays an essential role in determining the objective and selecting the object that satisfies the established need.     

Detecting anonymous attacks in wireless communication medium using adaptive grasshopper optimization algorithm

Intrusion Detection Systems (IDSs) is a system that monitors network traffic for suspicious activity and issues alert when such activity is revealed. Moreover, the existing IDSs-based methods are based on outdated attacks that unable to identify modern attacks or malicious trends. For this reason, in this study we developed a new multi-swarm adaptive grasshopper optimization algorithm to utilize adaptation mechanism in a group of swarms based on fuzzy logic to protect against sophisticated attacks. The proposed (MSAGOA) technique has the capability of global optimization and rapid convergence that are used to attain optimal feature subsets to identify attack types on IDS datasets. In the MSAGOA technique, learning engine as Extreme learning Machine, Naive Bayes, Random Forest and Decision Tree is applied as a fitness function to select the highly discriminating features and to maximize classification performance. Afterward, select the best classifier which works as a fitness function in our approach to measure the performance in terms of accuracy, detection rate, and false alarm rate. The simulations are performed on three IDS datasets such as NSL-KDD, AWID-ATK-R, and NGIDS-DS. The experimental results demonstrated that MSAGOA method has performed better and obtained high detection rate of 99.86%, accuracy of 99.89% in NSL-KDD and high detection rate of 98.73%, accuracy of 99.67% in AWID-ATK-R and detection rate of 89.50%, accuracy of 90.23% in NGIDS-DS. In addition, the performance is compared with several other existing techniques to show the efficacy of the proposed approach.