Humans do not always act selfishly: social identity and helping in emergency evacuation simulation

To monitor and predict the behaviour of a crowd, it is imperative that the technology used is based on an accurate understanding of crowd psychology. However, most simulations of evacuation scenarios rely on outdated assumptions about the way people behave or only consider the locomotion of pedestrian movement. We present a social model for pedestrian simulation based on self-categorisation processes during an emergency evacuation. We demonstrate the impact of this new model on the behaviour of pedestrians and on evacuation times. In addition to the Optimal Steps Model for locomotion, we add a realistic social model of collective behaviour

Institutions, sustainable land use and consumer welfare: the case of forest and grazing lands in northern Ethiopia

Land is an essential factor of production. Institutions that govern its efficient use determine the sustainability of this essential resource. In Ethiopia all land is publicly owned. Such an institutional setting is said to have resulted in the major degradation of Ethiopia's land resources and dissipation of the resource rent. An alternative to this is assigning a private property institution. In this paper, we examine the consumer welfare effects of a change in the institutional setting on communal forest and grazing lands, using a cross-section data set of 200 households in Northern Ethiopia. Findings suggest that changing the current institutional setting could indeed be welfare reducin

Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects

While monolithic satellite missions still pose significant advantages in terms of accuracy and operations, novel distributed architectures are promising improved flexibility, responsiveness, and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite networks or heterogeneous constellations hybridizing small-spacecraft nodes with highperformance satellites are becoming feasible and advantageous alternatives requiring the adoption of new operation paradigms that enhance their autonomy. While autonomy is a notion that is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic in Distributed Satellite Systems (DSS). In this context, this paper focuses on the motivations for system-level autonomy in DSS and justifies its need as an enabler of system qualities. Autonomy is also presented as a necessary feature to bring new distributed Earth observation functions (which require coordination and collaboration mechanisms) and to allow for novel structural functions (e.g., opportunistic coalitions, exchange of resources, or in-orbit data services). Mission Planning and Scheduling (MPS) frameworks are then presented as a key component to implement autonomous operations in satellite missions. An exhaustive knowledge classification explores the design aspects of MPS for DSS, and conceptually groups them into: components and organizational paradigms; problem modeling and representation; optimization techniques and metaheuristics; execution and runtime characteristics and the notions of tasks, resources, and constraints. This paper concludes by proposing future strands of work devoted to study the trade-offs of autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that consider some of the limitations of small spacecraft technologies.Postprint (author's final draft

Self-organising agent communities for autonomic resource management

The autonomic computing paradigm addresses the operational challenges presented by increasingly complex software systems by proposing that they be composed of many autonomous components, each responsible for the run-time reconfiguration of its own dedicated hardware and software components. Consequently, regulation of the whole software system becomes an emergent property of local adaptation and learning carried out by these autonomous system elements. Designing appropriate local adaptation policies for the components of such systems remains a major challenge. This is particularly true where the system’s scale and dynamism compromise the efficiency of a central executive and/or prevent components from pooling information to achieve a shared, accurate evidence base for their negotiations and decisions.In this paper, we investigate how a self-regulatory system response may arise spontaneously from local interactions between autonomic system elements tasked with adaptively consuming/providing computational resources or services when the demand for such resources is continually changing. We demonstrate that system performance is not maximised when all system components are able to freely share information with one another. Rather, maximum efficiency is achieved when individual components have only limited knowledge of their peers. Under these conditions, the system self-organises into appropriate community structures. By maintaining information flow at the level of communities, the system is able to remain stable enough to efficiently satisfy service demand in resource-limited environments, and thus minimise any unnecessary reconfiguration whilst remaining sufficiently adaptive to be able to reconfigure when service demand changes

Measuring Individuals\u27 Concerns over Collective Privacy on Social Networking Sites

With the rise of social networking sites (SNSs), individuals not only disclose personal information but also share private information concerning others online. While shared information is co-constructed by self and others, personal and collective privacy boundaries become blurred. Thus there is an increasing concern over information privacy beyond the individual level. Drawing on the Communication Privacy Management theory, we conceptualize individuals\u27 concerns over collective privacy on SNSs, with three distinctive dimensions—collective information access, control and diffusion, and develop a scale of collective SNS privacy concern (SNSPC) through empirical validation. Structural model analyses confirm the three-dimension structure of collective SNSPC and indicate perceived risk and propensity to value privacy as two antecedents. We discuss key findings, implications and future research directions for theorizing and examining privacy as a collective issue