Cognitive modeling of social behaviors

To understand both individual cognition and collective activity, perhaps the greatest opportunity today is to integrate the cognitive modeling approach (which stresses how beliefs are formed and drive behavior) with social studies (which stress how relationships and informal practices drive behavior). The crucial insight is that norms are conceptualized in the individual mind as ways of carrying out activities. This requires for the psychologist a shift from only modeling goals and tasks —why people do what they do—to modeling behavioral patterns—what people do—as they are engaged in purposeful activities. Instead of a model that exclusively deduces actions from goals, behaviors are also, if not primarily, driven by broader patterns of chronological and located activities (akin to scripts). To illustrate these ideas, this article presents an extract from a Brahms simulation of the Flashline Mars Arctic Research Station (FMARS), in which a crew of six people are living and working for a week, physically simulating a Mars surface mission. The example focuses on the simulation of a planning meeting, showing how physiological constraints (e.g., hunger, fatigue), facilities (e.g., the habitat’s layout) and group decision making interact. Methods are described for constructing such a model of practice, from video and first-hand observation, and how this modeling approach changes how one relates goals, knowledge, and cognitive architecture. The resulting simulation model is a powerful complement to task analysis and knowledge-based simulations of reasoning, with many practical applications for work system design, operations management, and training

Measuring interaction: An empirical comparison of three OLS regression models

The capacity to correctly assess the existence of interaction is a high-value modeling capability among researchers of information systems (IS), especially those focusing on behavioural paradigm studies. Interaction is a notable aspect for the major theoretical frameworks of the IS field, particularly the adoption theories. Allowing for crossover effects in the Theory of Planned Behaviour resulted in improvements in model prediction (Taylor & Todd, 1995b). This study presents the trimmed model, which does not permit crossover effect relations among variables. In complex models, as mentioned by Pedhazur (1997), one variable may affect another variable indirectly through multiple paths. According to him, it stands to reason that indirect effects, through certain paths, may be more meaningful and/or stronger than others. The findings of this quantitative study lead one to conclude that crossover effect models are more capable of showing the interaction among models’ variables, as well as explaining the highest percentage of variation for a single dependent variable, in comparison to the full and trimmed model

Purchase intention of specialty coffee

The main aims of this study are: (1) to test whether the theory of planned behavior (TPB) is useful to explain the intention to purchase specialty co ee; (2) to analyze whether people more involved in social responsibility could manifest a di erent response from those not so interested in this matter concerning specialty co ee. The sample is composed of 489 specialty co ee consumers from Brazil. The statistical tool for testing the measurement and structural model was partial least squares. Then a multigroup analysis was performed to meet the second objective; the software SmartPLS was utilized. The main contributions of this study are that we can explain the intention to use specialty coffee in a sample of Brazilian consumers using the classical TPB model. Moreover, we demonstrate the moderating e ect of consumer perception of corporate social responsibility in this general model

How to Educate Entrepreneurs?

Entrepreneurship education has two purposes: To improve students’ entrepreneurial skills and to provide impetus to those suited to entrepreneurship while discouraging the rest. While entrepreneurship education helps students to make a vocational decision its effects may conflict for those not suited to entrepreneurship. This study shows that vocational and the skill formation effects of entrepreneurship education can be identified empirically by drawing on the Theory of Planned Behavior. This is embedded in a structural equation model which we estimate and test using a robust 2SLS estimator. We find that the attitudinal factors posited by the Theory of Planned Behavior are positively correlated with students’ entrepreneurial intentions. While conflicting effects of vocational and skill directed course content are observed in some individuals, overall these types of content are complements. This finding contradicts previous results in the literature. We reconcile the conflicting findings and discuss implications for the design of entrepreneurship courses

Cellular-Automata Based Qualitative Simulation for Nonprofit Group Behavior

A cellular automata based qualitative simulation of group behavior (referred hitherto as \'loyalty to group\') will be presented by integrating QSIM (Qualitative SIMulation) and CA (Cellular Automata) modeling. First, we provide a breakdown of the structure of a group and offer an analysis of how this structure impacts behavior. The characteristics and impact had by anomalies within a group and by environmental factors are also explored. Second, we explore the transition between cause and effect (referred hitherto as the \'transition rule\') and the change in behavior that is the result of this transition (referred hitherto as the \'successor behavior state\'). A filter for weeding out anomalies is then proposed. The simulation engine is then used integrating all relevant data as outlined above. A concept referred to as the \'Loyalty-cost equilibrium\' is presented and factored into the filter. Third, the validity of this method is tested by running the simulation using eight generalized examples. The input-output of each simulation run using these examples is consistent with what can reasonably be accepted to be true, thus demonstrating that the proposed method is valid. At this point we illustrate how the simulation is applied in context. Simulation outputs (effect on group behavior) at each time stage of two alternating changes in policy are compared to determine which policy would be the most advantageous. This demonstrates that this method serves as reliable virtual tool in the decision making difficulties of group management.Cellular Automata; Qualitative Simulation; Group Behavior; Loyalty-Cost Equilibrium; Loyalty Gravitation; Cost Gravitation

Compliance with Social Norms as an Evolutionary Stable Equilibrium

Producción CientíficaThis paper studies a two-population evolutionary game in a new setting in between a symmetric and an asymmetric evolutionary model. It distinguishes two types of agents: Sanchos, whose payoffs are defined by a prisoner’s dilemma game, and Quixotes, whose payoffs are defined by a snowdrift game. Considering an imita- tive revision protocol, a revising agent is paired with someone from his own popula- tion or the other population. When matched, they observe payoffs, but not identities. Thus, agents in one population interact and imitate agents from their own population and from the other population. In this setting we prove that a unique mixed-strategy asymptotically stable fixed point of the evolutionary dynamics exists. Taking as an example the compliance with social norms, and depending on the parameters, two type of equilibrium are possible, one with full compliance among Quixotes and par- tial compliance among Sanchos, or another with partial compliance among Quixotes and defection among Sanchos. In the former type, Sanchos comply above their Nash equilibrium (as they imitate compliant Quixotes). In the latter type, Quixotes comply below their Nash equilibrium (as they imitate defecting Sanchos).This study was funded by the Spanish Government (projects ECO2014- 52343-P and ECO2017-82227-P), as well as financial aid from Junta de Castilla y León (projects VA024P17 and VA105G18), co-financed by FEDER funds

Are Accuracy and Robustness Correlated?

Machine learning models are vulnerable to adversarial examples formed by applying small carefully chosen perturbations to inputs that cause unexpected classification errors. In this paper, we perform experiments on various adversarial example generation approaches with multiple deep convolutional neural networks including Residual Networks, the best performing models on ImageNet Large-Scale Visual Recognition Challenge 2015. We compare the adversarial example generation techniques with respect to the quality of the produced images, and measure the robustness of the tested machine learning models to adversarial examples. Finally, we conduct large-scale experiments on cross-model adversarial portability. We find that adversarial examples are mostly transferable across similar network topologies, and we demonstrate that better machine learning models are less vulnerable to adversarial examples.Comment: Accepted for publication at ICMLA 201

On the uniqueness of solutions to the Gross-Pitaevskii hierarchy

We give a new proof of uniqueness of solutions to the Gross-Pitaevskii hierarchy, first established by Erdos, Schlein and Yau, in a different space, based on space-time estimates