On the current status of the evolutionary theory of behavior dynamics

The evolutionary theory of behavior dynamics is a complexity theory that instantiates the Darwinian principles of selection, reproduction, and mutation in a genetic algorithm. The algorithm is used to animate artificial organisms that behave continuously in time and can be placed in any experimental environment. The present paper is an update on the status of the theory. It includes a summary of the evidence supporting the theory, a list of the theory's untested predictions, and a discussion of how the algorithmic operations of the theory may correspond to material reality. Based on the evidence reviewed here, the evolutionary theory appears to be a strong candidate for a comprehensive theory of adaptive behavior.     

Out-of-bag Prediction Error: A Cross Validation Index for Generalized Structured Component Analysis

Cross validation is a useful way of comparing predictive generalizability of theoretically plausible a priori models in structural equation modeling (SEM). A number of overall or local cross validation indices have been proposed for existing factor-based and component-based approaches to SEM, including covariance structure analysis and partial least squares path modeling. However, there is no such cross validation index available for generalized structured component analysis (GSCA) which is another component-based approach. We thus propose a cross validation index for GSCA, called Out-of-bag Prediction Error (OPE), which estimates the expected prediction error of a model over replications of so-called in-bag and out-of-bag samples constructed through the implementation of the bootstrap method. The calculation of this index is well-suited to the estimation procedure of GSCA, which uses the bootstrap method to obtain the standard errors or confidence intervals of parameter estimates. We empirically evaluate the performance of the proposed index through the analyses of both simulated and real data.     

Why does impression management positively influence interview ratings? The mediating role of competence and warmth

Though interviews assess job applicants' skills and abilities, they can be influenced by extraneous factors, including impression management (IM) tactics. Interviewees’ self‐promotion and ingratiation IM tactics predict higher interview ratings; however, researchers have yet to determine why these tactics work. We assessed whether two fundamental dimensions of social perception, competence and warmth, mediate the relationship between IM tactics and interview ratings. We hypothesized that interviewee competence mediates the relationship between self‐promotion and interview ratings, and interviewee warmth mediates the relationship between ingratiation and interview ratings. Using real employment interviews, we found that competence mediates the relationship between self‐promotion and interview ratings, but warmth did not mediate the relationship between ingratiation and interview ratings in the way we expected.     

HIGH SCIENCE AND NATURAL SCIENCES: GREEK THEOLOGIANS AND THE SCIENCE AND RELIGION INTERACTIONS (1832–1910)

What was science for the Orthodox Greek theologian of the nineteenth century? How did it feature in his (theologians were all men at the time) own work? This article is an attempt to describe the science and religion interactions by placing Greek Orthodox theologians of the nineteenth century in the center of the historical narrative, rather than treat them as occasional deuteragonists in the scientists’ historiography. The picture that emerges is far more complicated than one of antagonism, indifference, conflict, or coexistence. Greek theologians saw themselves as scientists and treated theology as a positive, rational science. They developed strategies to delineate their disciplinary borders and safeguard their identity as expert scholars by harnessing their university and academic credentials. For that reason, they had to invoke famous German and other Western theologians, while ensuring that they were seen as true defenders of Orthodox Christianity. The idea of science was an integral part of this achievement.     

Children’s scale errors are a natural consequence of learning to associate objects with actions: A computational model

Young children sometimes attempt an action on an object, which is inappropriate because of the object size—they make scale errors. Existing theories suggest that scale errors may result from immaturities in children's action planning system, which might be overpowered by increased complexity of object representations or developing teleofunctional bias. We used computational modelling to emulate children's learning to associate objects with actions and to select appropriate actions, given object shape and size. A computational Developmental Deep Model of Action and Naming (DDMAN) was built on the dual‐route theory of action selection, in which actions on objects are selected via a direct (nonsemantic or visual) route or an indirect (semantic) route. As in case of children, DDMAN produced scale errors: the number of errors was high at the beginning of training and decreased linearly but did not disappear completely. Inspection of emerging object–action associations revealed that these were coarsely organized by shape, hence leading DDMAN to initially select actions based on shape rather than size. With experience, DDMAN gradually learned to use size in addition to shape when selecting actions. Overall, our simulations demonstrate that children's scale errors are a natural consequence of learning to associate objects with actions.     

Feature selection using Ant Colony Optimization (ACO) and Road Sign Detection and Recognition (RSDR) system

Road Sign Detection and Recognition (RSDR) is aimed to enable drivers maintain basic functionality with the aim of identifying and notifying driver through the existing restrictions so that the process is a success on the present widened road. Examples for RSDR include ‘traffic light ahead’ or ‘pedestrian crossing’ signs. An innovative RSDR system has been introduced which comprises of pre-processing, edge detection, feature extraction, features selection and Ensemble Fuzzy Support Vector Machine (EFSVM) classifier. Feature selection is carried out successfully by deployment of Ant Colony Optimization (ACO) algorithm to determine most prominent and definitive features. These features are then fed into the ensemble SVM to enable both road side traffic detection as well as recognition. Suggested system’s performance is analyzed and evaluated with respect to road signs having a capable recognition rate.     

How Otto did not extend his mind,but might have: Dynamic systems theory and social-cultural group selection

Proponents of cognitive Situationism argue that the human mind is embodied, embedded in both natural and social-cultural environments and extended creating both extended and distributed cognition. Anti-situationists reject all or some of these claims. I argue that four major objections to extended cognition: (1) the mark of the cognitive, (2) the function-identity fallacy, (3) cognitive bloat, and (4) scientific irrelevance lose much of their sting in the case of distributed cognition, the extension of cognitive agency to a group of cognitive agents, such as a scientific research team. However, I claim that a crucial fifth challenge, that advocates of the extended mind commit the causal-constitution fallacy, has yet to be satisfactorily addressed. I focus on Spyridon Palermos’ use of dynamic systems theory to refute this charge and I argue that his appeal to dynamic systems theory as a way of understanding system-constitution fails. Instead, I suggest a social-cultural group selection hypothesis for understanding system-constitution. But, I leave it for another day to elaborate that hypothesis’ empirical plausibility.     

The psychological coping,learning potential and career preferences profiles of operational force military candidates

The aim of this study was to profile the psychological coping, learning potential and career-related interests of 251 candidates for operational force military selection for the South African National Defence Force (SANDF) – 26 of whom were successful in the selection. Data on their sense of meaning, learning potential and career-related interest were gathered using standardised measures supplemented with open-ended responses. The data were analysed to compare the profiles of the successful candidates against those not selected. The selected group showed significantly higher mean scores on meaningfulness and learning potential, and lower scores for career-related interest in law and medicine. Findings suggest that psychological coping, learning potential and career-related preference information can be used to refine the selection of operational force military candidates.