Fig 1: Building connections among sources using a dynamic system. . Reasoning is dynamic and spatial. Whether escaping a war zone or watching a suspenseful movie, a person’s understanding of the real world changes over time and space. If machines could present knowledge as we understand it, they’d allow us to immersively connect fragments of[…]

               Beth Cardier, Patric Lundberg, Richard Ciavarra and Larry Sanford, Eastern Virginia Medical School. Saikou Diallo, John Shull, and Alex Nielsen, Virginia Modeling Analytics and Simulation Center, Old Dominion University. Ted Goranson, Griffith University, Australia. Niccolo Casas, RISD Rhode Island School of Design; The Barlett College, University College of London

Fig 1: Click photo to see the video: representing fluid knowledge using a dynamic system. . Reasoning is dynamic. Whether escaping a war zone or watching a suspenseful movie, a person’s understanding of the open world changes over time. If machines could adapt their knowledge as we do, perhaps they could detect unexpected causes of disease.[…]

The following videos show some basic aspects of the tool working. Using the Tool In fig. 1, below, nodes can be situated and moved, either individually or as a group. Links persistently follow the node. Fig 1. User within tool 1. In 3D, shadows and lighting are an issue. Fig. 2 shows our current solution,[…]

Click on image to expand, hover to discover the artist. Click on video to play. Alessio Erioli, Ted Goranson

How can we represent collective phenomena? Whether systems biology or open-world comprehension, such complexity is difficult to monitor or even envisage. Most formal approaches are supported by reductionist analytical models, which struggle to capture collective properties such as situated interactions or collaborative influence (Devlin, 2009). This project uses a narrative-based model of higher-level emergence to extend current approaches to modeling the[…]