In Search of Stars: Network Formation among Heterogeneous Agents

This paper reports the results of a laboratory experiments on network formation among heterogeneous agents. The experimental design extends the basic Bala-Goyal (2000) model of network formation with decay and two-way flow of benefits by allowing for agents with lower linking costs or higher benefits to others. We consider treatments where agents’ types are common knowledge and treatments where agents’ types are private information. In all treatments, the (efficient) equilibrium network has a “star” structure. We find that with homogeneous agents, equilibrium predictions fail completely. In Contrast, with heterogeneous agents stars frequently occur, often with the high-value or low- cost agent in the center. Stars are not borne but rather develop: in treatments with a high-value agents, the network’s centrality, stability, and efficiency all increase over time. Our results suggest that agents’ heterogeneity is a major determinant for the predominance of star-like structures in real-life social networks.microeconomics ;

In Search of Stars: Network Formation among Heterogeneous Agents

This paper reports results from a laboratory experiment on network formation among heterogeneous agents. The experimental design extends the Bala-Goyal (2000) model of network formation with decay and two-way flow of benefits by allowing for agents with lower linking costs or higher benefits to others. Furthermore, agents’ types may be common knowledge or private information. In all treatments, the (efficient) equilibrium network has a “star” structure. With homogeneous agents, equilibrium predictions fail completely. In contrast, with heterogeneous agents stars frequently occur, often with the high-value or low-cost agent in the center. Stars are not born but rather develop: with a high-value agent, the network’s centrality, stability, and efficiency all increase over time. Probit estimations based on best-response behaviour and other-regarding preferences are used to analyze individual linking behavior. Our results suggest that heterogeneity is a major determinant for the predominance of star-like structures in real-life social networks.Network Formation, Experiment, Heterogeneity, Private Information

A Lightweight Intelligent Virtual Cinematography System for Machinima Production

Machinima is a low-cost alternative to full production filmmaking. However, creating quality cinematic visualizations with existing machinima techniques still requires a high degree of talent and effort. We introduce a lightweight artificial intelligence system, Cambot, that can be used to assist in machinima production. Cambot takes a script as input and produces a cinematic visualization. Unlike other virtual cinematography systems, Cambot favors an offline algorithm coupled with an extensible library of specific modular and reusable facets of cinematic knowledge. One of the advantages of this approach to virtual cinematography is a tight coordination between the positions and movements of the camera and the actors

Toward Intelligent Support of Authoring Machinima Media Content: Story and Visualization

The Internet and the availability of authoring tools have enabled a greater community of media content creators, including nonexperts. However, while media authoring tools often make it technically feasible to generate, edit and share digital media artifacts, they do not guarantee that the works will be valuable or meaningful to the community at large. Therefore intelligent tools that support the authoring and creative processes are especially valuable. In this paper, we describe two intelligent support tools for the authoring and production of machinima. Machinima is a technique for producing computer-animated movies through the manipulation of computer game technologies. The first system we describe, ReQUEST, is an intelligent support tool for the authoring of plots. The second system, Cambot, produces machinima from a pre-authored script by manipulating virtual avatars and a virtual camera in a 3D graphical environment

Did domestic violence really increase in the early phase of the COVID-19 pandemic?:Results of an interview-based observational study

Objectives: The COVID-19 lockdown may lead to rising numbers of domestic violence (DV), especially among previously victimized individuals. The aim of this study was to investigate the development and influential factors of DV during the early COVID-19 lockdown. Methods: In this telephone-based study, previous participants with (n = 34) and without (n = 33) DV completed questionnaires on DV, attachment and COVID-19 related stressors. Development of DV and influential factors were investigated with repeated measures ANOVAs and linear regression models. Results: Individuals with prior DV reported significantly higher DV than previously not affected individuals. However, a statistically significant decrease of DV was found in the group with prior DV. Past DV, childlessness and insecure attachment, but not COVID-19 related stressors predicted current DV. Conclusions: In light of an insecure attachment style lockdown measures may have led to a temporary relationship stabilization. However, a reassessment is necessary to evaluate whether this stabilization was a short-time trend only