Andreas Tolk

Intelligent defence support systems are confronted with the need to manage ever-increasing floods of data in a way that raises significant challenges because the data are described and presented using different terminologies and formats. How, on this basis, is it possible to reach a common understanding of the information content of these data among people and software agents? How is it possible to ensure that domain knowledge is reused in consistent fashion in a way that makes this information available for integration and analysis? How can we support the identification, selection, composition, and orchestration of services based on such diverse data providing homogeneous support by a service-oriented architecture? This collection is devoted to the use of ontologies to answer questions such as these.

The social sciences and humanities are fragmented into specialized areas, each with their own parlance and procedures. This hinders information sharing and the growth of a coherent body of knowledge. Modeling and simulation can be the scientific lingua franca, or shared technical language, that can unite, integrate, and relate relevant parts of these diverse disciplines.Models are well established in the scientific community as mediators, contributors, and enablers of scientific knowledge. We propose a potentially revolutionary linkage between social sciences, humanities and computer simulation, forging what we call “human simulation.” We explore three facets of human simulation, namely: the simulation of humans, the design of simulations for human use, and simulations that include humans as well as simulated agents among the actors. We describe the potential of human simulation using several illuminating examples. We also discuss computational, epistemological, and hermeneutical challenges constraining the use of human simulation.

Operating universities under pandemic conditions is a complex undertaking. The Artificial University responds to this need. TAU is a configurable, open-source computer simulation of a university using a contact network based on publicly available information about university classes, residences, and activities. This study evaluates health outcomes for an array of interventions and testing protocols in an artificial university of 6,500 students, faculty, and staff. Findings suggest that physical distancing and centralized contact tracing are most effective at reducing infections, but there is a tipping point for compliance below which physical distancing is less effective. If student compliance is anything short of high, it helps to have separate buildings for quarantining infected students, thereby gracefully increasing compliance. Hybrid in-person and online classes and closing fitness centers do not significantly change cumulative infections but do significantly decrease the number of the infected at any given time, indicating strategies for “flattening the curve” to protect limited resources. Supplementing physical distancing with centralized contact tracing decreases infected individuals by an additional 14%; boosting frequency of testing for student-facing staff yields a further 7% decrease. A trade-off exists between increasing the sheer number of infection tests and targeting testing for key nodes in the contact network. There are significant advantages to getting and acting on test results quickly. The costs and benefits to universities of these findings are discussed. Artificial universities can be an important decision support tool for universities, generating useful policy insights into the challenges of operating universities under pandemic conditions.

This uniquely inspirational and practical book explores human simulation, which is the application of computational modeling and simulation to research subjects in the humanities disciplines. It delves into the fascinating process of collaboration among experts who usually don’t have much to do with one another – computer engineers and humanities scholars – from the perspective of the humanities scholars. It also explains the process of developing models and simulations in these interdisciplinary teams. Each chapter takes the reader on a journey, presenting a specific theory about the human condition, a model of that theory, discussion of its implementation, analysis of its results, and an account of the collaborative experience. Contributing authors with different fields of expertise share how each model was validated, discuss relevant datasets, explain development strategies, and frankly discuss the ups and downs of the process of collaborative development. Readers are given access to the models and will also gain new perspectives from the authors’ findings, experiences, and recommendations. Today we are in the early phases of an information revolution, combining access to vast computing resources, large amounts of human data through social media, and an unprecedented richness of methods and tools to capture, analyze, explore, and test hypotheses and theories of all kinds. Thus, this book’s insights will be valuable not only to students and scholars of humanities subjects, but also to the general reader and researchers from other disciplines who are intrigued by the expansion of the information revolution all the way into the humanities departments of modern universities.