相关论文: A methodology for co-constructing an interdiscipli…
Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development. The understanding of socioeconomic processes provides foundations to quantify global economic…
Mathematical models of complex social systems can enrich social scientific theory, inform interventions, and shape policy. From voting behavior to economic inequality and urban development, such models influence decisions that affect…
The nature of information security has been, and probably will continue to be, marked by the asymmetric competition of attackers and defenders over the control of an uncertain environment. The reduction of this degree of uncertainty via an…
Studies of human-robot interaction in dynamic and unstructured environments show that as more advanced robotic capabilities are deployed, the need for cooperative competencies to support collaboration with human problem-holders increases.…
Nowadays the composition and formation of effective teams is highly important for both companies to assure their competitiveness and for a wide range of emerging applications exploiting multiagent collaboration (e.g. crowdsourcing,…
Dialogue-based human-AI collaboration can revolutionize collaborative problem-solving, creative exploration, and social support. To realize this goal, the development of automated agents proficient in skills such as negotiating, following…
What do societies, the Internet, and the human brain have in common? They are all examples of complex relational systems, whose emerging behaviours are largely determined by the non-trivial networks of interactions among their constituents,…
Interactive communication (IC), i.e., the reciprocal exchange of information between two or more interactive partners, is a fundamental part of human nature. As such, it has been studied across multiple scientific disciplines with different…
Interdisciplinary collaboration is essential for the advance of research. As domain subjects become more and more specialized, researchers need to cross disciplines for insights from peers in other areas to have a broader and deeper…
Group interactions take place within a particular socio-temporal context, which should be taken into account when modelling interactions in online communities. We propose a method for jointly modelling community structure and language over…
It is natural for humans to collaborate while dealing with complex problems. In this article I consider this process of collaboration in the context of information seeking. The study and discussion presented here are driven by two…
Developing artificial intelligence (AI) tools for healthcare is a collaborative effort, bringing data scientists, clinicians, patients and other disciplines together. In this paper, we explore the collaborative data practices of research…
A subjective expected utility policy making centre, managing complex, dynamic systems, needs to draw on the expertise of a variety of disparate panels of experts and integrate this information coherently. To achieve this, diverse supporting…
We propose and define the construct, cross-disciplinary learning, which can guide learning and assessment in programs that feature sequential learning across multiple STEM disciplines. Cross-disciplinary learning combines insights from…
Eye contact between individuals is particularly important for understanding human behaviour. To further investigate the importance of eye contact in social interactions, portable eye tracking technology seems to be a natural choice.…
Both conceptual modeling and machine learning have long been recognized as important areas of research. With the increasing emphasis on digitizing and processing large amounts of data for business and other applications, it would be helpful…
We focus on collaborative activities that engage computer graphics designers and social scientists in systems design processes. Our conceptual symmetrical account of technology design and theory development is elaborated as a mode of mutual…
Large-scale neuroscience is generating rich datasets across animals, brain areas and behavioral contexts, yet our modeling efforts remains fragmented across isolated experiments. We argue that understanding behavior requires integrative…
Machine learning has been applied to a number of creative, design-oriented tasks. However, it remains unclear how to best empower human users with these machine learning approaches, particularly those users without technical expertise. In…
Learning from data has led to substantial advances in a multitude of disciplines, including text and multimedia search, speech recognition, and autonomous-vehicle navigation. Can machine learning enable similar leaps in the natural and…