Salvador Herrando

P-SPACE: a program for simulating spatial behavior in small groups.

P-SPACE is a computer program that simulates spatial behavior in a small group of individuals. The program describes how interpersonal distances change through time as a result of changes in microlevel features, such as the minimization of local dissatisfaction. Agents are located in a two-dimensional lattice and can move some discrete space units at each discrete time unit within their neighborhood. A nonsymmetrical matrix of ideal distances between agents must be specified. Agents move in order to minimize their dissatisfaction, defined as a function of the discrepancy between possible future distances and ideal distances between agents. At each iteration, agents will move to those cells in their neighborhoods for which the function is minimized. Depending on the specific values in the ideal-distance matrix, different kinds of social dynamics can be simulated.

An Index for Quantifying Flocking Behavior

One of the classic research topics in adaptive behavior is the collective displacement of groups of organisms such as flocks of birds, schools of fish, herds of mammals, and crowds of people. However, most agent-based simulations of group behavior do not provide a quantitative index for determining the point at which the flock emerges. An index was developed of the aggregation of moving individuals in a flock and an example was provided of how it can be used to quantify the degree to which a group of moving individuals actually forms a flock.

Measuring the Typicality of Objects Included in Environmental Scenes: A Logistic Model for Atypicality

Some empirical studies have stated that people usually categorize scenes according to the suitability of their elements. This paper proposes a method of measuring the typicality of naturalistic objects contained in environmental scenes. 517 subjects gave a score of suitability for 110 object-scene pairs. We used a logistic model for the measurements which enabled us to obtain two indexes, atypicality and discrimination. Analysis showed that the objects could be arranged on a numerical scale according to their typicality in a scene, and from this we concluded that logistic models are a useful and powerful method of measuring typicality.

Measuring the Typicality of Objects Included in Environmental Scenes: A First Scale

Many researchers have been using the concept of “typicality” to explain the influence of knowledge structures on processing visual stimuli. In this paper we try to establish a preliminary method for measuring the typicality of natural objects contained in environmental scenes. The results are discussed in the context of research on how objects in scenes are identified. We also suggest that scales of typicality continue to be developed.

Typicality of Objects in Environmental Scenes: Effects of Stimuli

The norms of typicality for objects included in scenes can be obtained by showing a set of paired scenes and objects and asking subjects to rate their typicality on a scale from 1 to 5. However, it is necessary to know whether the presence or absence of the object in the scene influences this judgement. We showed scene-object pairs within equivalent scenes and with or without objects of varying typicality to 56 subjects. Analysis showed the influence of including the object in the scene when the typicality is judged at the lowest values of the scale.

Social Simulation Based on Cellular Automata: Modeling Language Shifts

Nowadays, language shifts (i.e., a community of speakers stops using their traditional language and speaks a new one in all communication settings) may produce a massive extinction of languages throughout the world. In this context, an important task for social sciences research should therefore be to achieve a deep comprehension of language shifts. However, modeling the social and behavioral variables that guide the social behavior of individuals and groups has traditionally been tricky in all the social sciences. In this situation, social simulation provides a tool for testing hypotheses and building models of social phenomena (see, for example, Gilbert, 1996; Gilbert & Toitzsch, 2005; and Goldspink, 2002), especially the techniques based on cellular automata theory (Hegselmann, 1996; Hegselman & Flache, 1998; Nowak & Lewenstein, 1996). According to this framewok, we introduce the properties of a cellular automaton that incorporates some assumptions from the Gaelic-Arvanitika model of language shifts (Sasse, 1992) and the findings on the dynamics of social impacts in the field of social psychology (Latane, 1981; Nowak et al. 1990). Thus, we define a cellular automaton and carry out a set of simulations in which it is used. We incorporate empirical data from recent sociolinguistic studies in Catalonia (a region in Southern Europe) to run the automaton under different scenarios. The results allow us to highlight some of the main factors involved in a language shift. Finally, we also discuss how the social simulation based on cellular automata theory approach proves to be a useful tool for understanding language shifts.

TYPICALITY OF OBJECTS IN URBAN PARK SCENES

Typicality is a basic property of any categorization process, including the categorization of environmental scenes. We tried to judge whether a scene as a type of situation influences judgements about the typicality of elements when considering the part-whole relationship between the element and the scene. The subjects were asked to rate typicality on a scale of 1 to 7 and to give a word that defined the urban park elements appearing in a park scene or on a blank background. Some elements (wastepaper basket, fountain, street lamp, and statue) were depicted with two styles (classical and contemporary). The results indicate that the scene or blank background had no effect on the typicality scores but subjects had difficulty providing an appropriate word when elements with a contemporary style were shown on a blank background.