Travel: a long-range goal of retired women

The authors surveyed retired persons (predominately women) with regard to their immediate, intermediate, and long-range activities following retirement. As predicted, leisure travel emerged as a frequent long-range goal for persons retired more than 5 years. The travel activity preferences of long-retired older women present challenges and opportunities to both researchers and marketers. Length of trips and frequency of trips have been predicted from regression models, with trip length in particular being well predicted by the problem of daily life hassles. A theoretical model of continued post-retirement travel is presented as a variant of Solomon's opponent process theory of affect (R. L. Solomon, 1980). The authors suggest that to the degree that places traveled to are varied and different, older people may remain stimulated and continue to enjoy retirement.     

Development of a Spanish version of the Participation Motivation Inventory for young competitive swimmers

The present study examined the validity of a Spanish version of the Participation Motivation Inventory, modified for swimming by Gould, Feltz, and Weiss in 1985, and investigated whether young swimmers differing in sex and age vary in their objectives for participation. Swimmers (204 boys and 224 girls, ranging in age from 8 to 22 years) were administered the inventory. Factor analysis with varimax rotation identified seven factors fairly consistent with previous research. Differences were found across age and sex. Females placed greater emphasis than males on Friendship and Fun and indicated lower importance rating to Status. Younger children (8-10 years) rated Fun/Friendship, Competition/Skills, Significant Others, and Status significantly higher in importance than did the other age groups.     

A methodology for describing and decomposing complex psychosocial and behavioral interventions

This article presents a comprehensive conceptual framework and methodology for characterizing multidimensional psychosocial and behavioral interventions for family caregivers of people with Alzheimer's disease. The methodology involved conducting a detailed task analysis of the interventions, and the application of the analytical hierarchy process. The authors were able to achieve high levels of consistency and reliability using this methodology to decompose and describe the interventions according to a complex conceptual framework comprising 3 dimensions: target domain, functional domain, and delivery system characteristics. Application of this methodology will enhance the ability to describe and measure interventions consistently, make comparisons across studies, isolate causal factors that achieve desired outcomes, and more generally elevate the science of psychosocial intervention research.     

Uncertainty in pigeons

Pigeons classified a display of illuminated pixels on a touchscreen as sparse or dense. Correct responses were reinforced with six food pellets; incorrect responses were unreinforced. On some trials an uncertain response option was available. Pecking it was always reinforced with an intermediate number of pellets. Like monkeys and people in related experiments, the birds chose the uncertain response most often when the stimulus presented was difficult to classify correctly, but in other respects their behavior was not functionally similar to human behavior based on conscious uncertainty or to the behavior of monkeys in comparable experiments. Our data were well described by a signal detection model that assumed that the birds were maximizing perceived reward in a consistent way across all the experimental conditions.     

The role of the centre of projection in the estimation of slant from texture of planar surfaces

Displays were presented consisting of a perspective projection of a regular square grid, made up of vertical and horizontal equally spaced white lines, that was slanted in depth. The surface was viewed monocularly, through a circular aperture. A range of slants was shown (0 degree, 10 degrees, 20 degrees, 30 degrees, 40 degrees, 50 degrees, or 60 degrees) and the observers' task was to match the slant by means of a mouse-driven probe. The viewing distance (50, 75, or 100 cm) as well as the focal distance (25, 50, 75, 100, or 125 cm) were varied. We expected the estimation error to be smallest when the viewing distance and the focal distance coincided. This was not the case. Instead, subjects seemed to use the perspective deformation of the texture elements in the stimulus display to make a slant estimation, regardless of the specific combination of viewing distance and focal distance.     

Visual perspective taking for avatars in a Simon task

In modern digital applications, users often interact with virtual representations of themselves or others, called avatars. We examined how these avatars and their perspectives influence stimulus–response compatibility in a Simon task. Participants responded to light/dark blue stimuli with left/right key presses in the presence of a task-irrelevant avatar. Changes in stimulus–response compatibility were used to quantify changes in the mental representation of the task and perspective taking toward this avatar. Experiments 1 and 2 showed that perspective taking for an avatar occurred in orthogonal stimulus–response mappings, causing a compatibility effect from the avatar’s point of view. In the following two experiments we introduced a larger variety of angular disparities between the participant and avatar. In Experiment 3, the Simon effect with lateralized stimulus positions remained largely unaffected by the avatar, pointing toward an absence of perspective taking. In Experiment 4, after avatar hand movements were added in order to strengthen the participants’ sense of agency over the avatar, a spatial compatibility effect from the avatar’s perspective was observed again, and hints of the selective use of perspective taking on a trial-by-trial basis were found. Overall, the results indicate that users can incorporate the perspective of an avatar into their mental representation of a situation, even when this perspective is unnecessary to complete a task, but that certain contextual requirements have to be met.     

Knowledge level learning and the power law: A soar model of skill acquisition in scheduling

Zusammenfassung. Das hier vorgestellte Modell lernt graduell, Planungsaufgaben aus der Klasse der Maschinenbelegungsprobleme (job-shop-scheduling problems) zu lösen. Mit Hilfe des Chunking-Mechanismus von Soar wird episodisches Wissen über die Belegungsreihenfolge von Aufträgen auf Maschinen memoriert. Bei der Entwicklung des Modells wurden zahlreiche qualitative (z. B. Transfereffekte) und quantitative Befunde (z. B. Bearbeitungszeiten) aus einer früheren empirischen Untersuchung berücksichtigt. In einer Validierungsstudie wurden dieselben Aufgaben von 14 Probanden und dem Modell bearbeitet. Die Passung von Simulationsdaten und empirischen Ergebnissen fiel insgesamt gut aus. Allerdings löst das Modell die Aufgaben schneller und zeigt auch einen etwas besseren Lernverlauf als die Probanden. Das Modell liefert eine Erklärung für das Rauschen, das typischerweise bei Bearbeitungszeiten zu beobachten ist: es handelt sich um erworbenes Wissen, das mehr oder weniger gut und auch unterschiedlich häufig auf neue Situationen übertragen wird. Der Lernverlauf der Probanden entspricht nur für aggregierte Daten einer Potenzfunktion (power law). Der vorgestellte Mechanismus zeigt, wie ein symbolisches Modell der Informationsverarbeitung graduelle Verhaltensänderungen generiert und wie der offensichtliche Erwerb allgemeiner Prozeduren ohne explizites Lernen von deklarativen Regeln erfolgen kann. Es wird nahegelegt, daß es sich hier um die Modellierung einer Form impliziten Lernens handelt. Summary. The model presented here gradually learns how to perform a job-shop scheduling task. It uses Soar's chunking mechanism to acquire episodic memories about the order to schedule jobs. The model was based on many qualitative (e.g., transfer effects) and quantitative (e.g., solution time) regularities found in previously collected data. The model was tested with new data where scheduling tasks were given to the model and to 14 subjects. The model generally fit these data with the restrictions that the model performs the task (in simulated time) faster than the subjects, and its performance improves somewhat more quickly than the subjects' performance. The model provides an explanation of the noise typically found in problem solving times - it is the result of learning actual pieces of knowledge that transfer more or less to new situations but rarely by an average amount. Only when the data are averaged (i.e., over subjects) does the smooth power law appear. This mechanism demonstrates how symbolic models can exhibit a gradual change in behavior and how the apparent acquisition of general procedures can be performed without resorting to explicit declarative rule generation. We suggest that this may represent a type of implicit learning.     

The puzzle of language evolution

Linguistics must again concentrate on the evolutionary nature of language, so that language models are more realistic with respect to human natural languages and have a greater explanatory force. Multi-agent systems are proposed as a possible route to develop such evolutionary models and an example is given of a concrete experiment in the origins and evolution of word-meaning based on a multi-agent approach.