Abstract: To study linguistically coded concepts, researchers often resort to the Property Listing Task (PLT). In a PLT, participants are asked to list properties that describe a concept (e.g., for DOG, subjects may list �is a pet�, �has four legs�, etc.). When PLT data is collected for many concepts, researchers obtain Conceptual Properties Norms (CPNs), which are used to study semantic content and as a source of control variables. Though the PLT and CPNs are widely used across psychology, only recently a model that describes the listing course of a PLT has been developed and validated. That original model describes the listing course using order of production of properties. Here we go a step beyond and validate the model using response times (RT), i.e., the time from cue onset to property listing. Our results show that RT data exhibits the same regularities observed in the previous model, but now we can also analyze the time course, i.e., dynamics of the PLT. As such, the RT validated model may be applied to study several similar memory retrieval tasks, such as the Free Listing Task, Verbal Fluidity Task, and to examine related cognitive processes. To illustrate those kinds of analyses, we present a brief example of the difference in PLT�s dynamics between listing properties for abstract versus concrete concepts, which shows that the model may be fruitfully applied to study concepts.

Abstract: This paper deals with the state estimation and control problem for nonlinear lateral vehicle dynamics with time delays. First, a novel time-varying delay vehicle model described as a Takagi-Sugeno fuzzy model is presented. In particular, it is considered that the lateral force contains an air resistance term which is assumed to be a quadratic function of the lateral vehicle velocity. A time-varying delay has been included in the vehicle states by a simple formula in order to capture brake actuation aspects or other practical aspects that may generate a delayed response, while the nonlinear part of the vehicle model is described as a Lipschitz function. A Takagi-Sugeno time-delay observer-based control that satisfies the Lipschitz condition is proposed to get closed-loop stability conditions. These results generalize existing ones in the literature on lateral dynamics control. Additionally, we provide a new methodology for the controller and observer gains design that can be cast as linear matrix inequality constraints. Finally, we illustrate our results with numerical examples, which also reveal the negative effect of not considering the presence of delays in the controller design.

Abstract: We use a feature-based association model to fit grouped and individual level category learning and transfer data. The model assumes that people use corrective feedback to learn individual feature to categorization-criterion correlations and combine those correlations additively to produce classifications. The model is an Adaptive Linear Filter (ALF) with logistic output function and Least Mean Squares learning algorithm. Categorization probabilities are computed by a logistic function. Our data span over 31 published data sets. Both at grouped and individual level analysis levels, the model performs remarkably well, accounting for large amounts of available variances. When fitted to grouped data, it outperforms alternative models. When fitted to individual level data, it is able to capture learning and transfer performance with high explained variances. Notably, the model achieves its fits with a very minimal number of free parameters. We discuss the ALF's advantages as a model of procedural categorization, in terms of its simplicity, its ability to capture empirical trends and its ability to solve challenges to other associative models. In particular, we discuss why the model is not equivalent to a prototype model, as previously thought.