Structural consequences of individual position in nondyadic social networks

The pattern of dyadic relationships among members of a population has often been used to obtain important information on the way that social structure can further or constrain social action. More recently, it has been proposed that nondyadic relationships can play a similar role. In this paper, a formalism is proposed that allows the dyadic structure and the nondyadic structure to be considered simultaneously. If this formalism is applied to the study of the structure arising from attendance at significant social events, it becomes possible to identify potential loci for social action. Still further, it is shown that information on individuals' structural perspectives with respect to such potential loci can be translated into conclusions about the individuals' positions in the dyadic structure. Such considerations can be used to evaluate the relative potential of these loci for social action.     

What is the answer? And come to that, what are the questions?

In recent years, the topic of car-following has become of increased importance in traffic engineering and safety research. Models of this phenomenon, which describe the interaction between (typically) adjacent vehicles in the same lane, now form the cornerstone for many important areas of research including (a) simulation modelling, where the car-following model (amongst others) controls the motion of the vehicles in the network, and (b) the functional definition of advanced vehicle control and safety systems (AVCSS), which are being introduced as a driver safety aid in an effort to mimic driver behaviour but remove human error. Despite the importance of this area however, no overview of the models availability and validity exists. It is the intent of this paper therefore to briefly assess the range of options available in the choice of car-following model, and assess just how far work has proceeded in our understanding of what, at times, would appear to be a simple process.     

Individual autonomy in organizations

This paper attempts to quantify the notion of an individual's desire for autonomy in an organization. It is shown that the basis for this concept can be formulated axiomatically, and a numerical function constituting the “degree” of autonomy can be derived. The relations between the individual's basic preferences, his/her feelings of autonomy, and the individual's performance as an organization member, are also studied. In this connection the loyalty of the member to the organization becomes important, and this notion is also developed axiomatically.     

航空模拟舱飞行行为的EPIC理论仿真

利用计算机技术,以执行过程交互控制(EPIC)理论框架为基础,建立了一个虚拟飞行员飞行过程的计算模型,并对人在复杂任务下的作业绩效进行了仿真。结果表明：(1)该研究在原有EPIC理论基础上发展的仿真模型合理可行;(2)仿真结果和实验结果拟合良好,模型具有良好的预测能力。该研究为以仿真方法研究复杂任务的心理过程提供了一次有益的尝试。     

ACACIA: an agent-based program for simulating behavior to reach long-term goals

We present ACACIA, an agent-based program implemented in Java StarLogo 2.0 that simulates a two-dimensional microworld populated by agents, obstacles and goals. Our program simulates how agents can reach long-term goals by following sensorial-motor couplings (SMCs) that control how the agents interact with their environment and other agents through a process of local categorization. Thus, while acting in accordance with this set of SMCs, the agents reach their goals through the emergence of global behaviors. This agent-based simulation program would allow us to understand some psychological processes such as planning behavior from the point of view that the complexity of these processes is the result of agent–environment interaction.