Towards agent-based crowd simulation in airports using games technology

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 evaluate the scalability with increasing number of agents demonstrating navigation behaviour

From individual characters to large crowds: augmenting the believability of open-world games through exploring social emotion in pedestrian groups

Crowds of non-player characters improve the game-play experiences of open-world video-games. Grouping is a common phenomenon of crowds and plays an important role in crowd behaviour. Recent crowd simulation research focuses on group modelling in pedestrian crowds and game-designers have argued that the design of non-player characters should capture and exploit the relationship between characters. The concepts of social groups and inter-character relationships are not new in social psychology, and on-going work addresses the social life of emotions and its behavioural consequences on individuals and groups alike. The aim of this paper is to provide an overview of current research in social psychology, and to use the findings as a source of inspiration to design a social network of non-player characters, with application to the problem of group modelling in simulated crowds in computer games

Attack on the clones: managing player perceptions of visual variety and believability in video game crowds

Crowds of non-player characters are increasingly common in contemporary video games. It is often the case that individual models are re-used, lowering visual variety in the crowd and potentially affecting realism and believability. This paper explores a number of approaches to increase visual diversity in large game crowds, and discusses a procedural solution for generating diverse non-player character models. This is evaluated using mixed methods, including a “clone spotting” activity and measurement of impact on computational overheads, in order to present a multi-faceted and adjustable solution to increase believability and variety in video game crowds

Does First Last: The Existence and Extent of First Mover Advantages on Spatial Networks

This paper examines the nature of first mover advantages on spatially-differentiated surface transportation networks. The literature on first mover advantages identifies a number of sources that explain their existence. However whether those sources exist on spatial networks, and how they play out with true capital immobility have been unanswered questions. By examining empirical examples including commuter rail and the Underground in London and roads in the Twin Cities of Minneapolis and St. Paul, first mover advantages were observed in rail stations but not in the road network. A simulation model was then constructed to replicate the growth of surface transportation networks incorporating idealized deployment decisions and to test whether the first network elements (links, nodes) remain strongest (or even strong) into the future. Simulation experiments were conducted and Spearman rank correlation tests revealed that first mover advantages exist in both nodes and links and become increasingly prominent as the network evolves due to the accumulated advantage of earlier established network elements. Simulation results also disclosed that network growth with a higher concentration of initial land uses results in stronger first mover advantages, and that the extent may vary as the topological attributes of the network change over time. The sensitivity of simulation results on model parameters are also discussed.First mover advantage, transport, land use, London Underground, London railways, network growth, induced demand, induced supply

MISER: Mise-En-Scène Region Support for Staging Narrative Actions in Interactive Storytelling

The recent increase in interest in Interactive Storytelling systems, spurred on by the emergence of affordable virtual reality technology, has brought with it a need to address the way in which narrative content is visualized through the complex staging of multiple narrative agents' behaviors within virtual story worlds. In this work we address the challenge of automating several aspects of staging the activities of a population of narrative agents and their interactions, where agents can have differing levels of narrative relevance within the situated narrative actions. Our solution defines an approach that integrates the use of multiple dynamic regions within a virtual story world, specified via a semantic representation that is able to support the staging of narrative actions through the behaviors of the primary and background agents' that are involved. This encompasses both the mechanics of dealing with the narrative discourse level as well as the interaction with the narrative generation layer to account for any dynamic modifications of the virtual story world. We refer to this approach as mise-en-scène region (miser) support. In this paper, we describe our approach and its integration as part of a fully implemented Interactive Storytelling system. We illustrate the work through detailed examples of short narrative instantiations. We present the results of our evaluation which clearly demonstrate the potential of the miser approach, as well as its scalability