Crowd-sourcing social computing systems represent a new material for HCI designers. Crowd sourcing has been successfully applied to many areas, but these systems are difficult to reliably design and prototype. One source of uncertainty during design is the behavior of the crowd at different levels of scale. A second source of uncertainty during design is the crowd’s response to differing incent...

Most crowd simulators focus on navigation and agents flow. In this paper, we present another perspective that concentrates on the overall distribution of virtual agents and uses psychological preferences for choosing goal locations. Both observation and published theory indicate that most people prefer to maintain their personal space as event spaces increase in density, particularly when they ...

Today, users are reading the news through social platforms. These platforms are built to facilitate crowd engagement, but not necessarily disseminate useful news to inform the masses. Hence, the news that is highly engaged with may not be the news that best informs. While predicting news popularity has been well studied, it has not been studied in the context of crowd manipulations. In this pap...

Crowd algorithms often assume workers are inexperienced and thus fail to adapt as workers in the crowd learn a task. These assumptions fundamentally limit the types of tasks that systems based on such algorithms can handle. This paper explores how the crowd learns and remembers over time in the context of human computation, and how more realistic assumptions of worker experience may be used whe...

The processing time to simulate crowds for games or simulations is a real challenge. While the increasing power of processing capacity is a reality in the hardware industry, it also means that more agents, better rendering and most sophisticated Artificial Intelligence (AI) methods can be used, so again the computational time is an issue. Despite the processing cost, in many cases the most inte...

This paper proposes a mathematical model and a computational approach to study the complex multiphysical non linear coupled system that results from the interaction between a moving platform and the pedestrians who walk on it. The described method is based on the mathematical and numerical decomposition of the coupled system into two subsystems and on the two-way interaction between them. In pa...

Modeling changes in individual relevance assessor performance over time offers new ways to improve the quality of relevance judgments, such as by dynamically routing judging tasks to assessors more likely to produce reliable judgments. Whereas prior assessor models have typically adopted a single generative approach, we formulate a discriminative, flexible feature-based model. This allows us to...

A simulation of crowd movement in a city is studied under various assumptions about interactions between people. We find, in general, that there are two modes of steady-state behavior. The crowd may be distributed across the city, or it may end up gathered in one place. A mathematical model describes the long-term behavior and shows that this change in behavior is sensitive to a critical parame...

We adapt popular video games technology for an agent-based crowd simulation in an airport terminal. To achieve this, we investigate the unique traits of airports and implement a virtual crowd by exploiting a scalable layered intelligence technique in combination with physics middleware and a socialforces approach. Our experiments show that the framework runs at interactive frame-rate and evalua...

If a robot can predict crowds in parts of its environment that are inaccessible to its sensors, then it can plan to avoid them. This paper proposes a fast, online algorithm that learns average crowd densities in different areas. It also describes how these densities can be incorporated into existing navigation architectures. In simulation across multiple challenging crowd scenarios, the robot r...