Research project In several sciences there is a shift towards complexities. E.g. in gene-expressions, in sick house syndrome, and in the brain. Single quasi-simple patterns have been proven to fail. Now we know that multitudes of variables work together even for single functions, but in incredibly complex ways. This has put demands on theoretical development as well as on quantitative methods, and this was recently highlighted in the latest Noble prize in physics to Giorgio Parisi (the bird flocks).
Today, we don’t know how to quantitatively identify when two systems become one, we call it the Soccer Game Problem. The main aim here is to develop AI to do this.
Umeå University
This grant will produce the following outputs through two working groups hosted by researchers at Umeå University with international-based collaborators. The working groups will address one of the most pressing questions in social neuroscience related to multi-brain systems. At its core the question is a classification problem of determining when two people form a single connected system versus two separate systems. There is a large body of qualitative and evolutionary evidence that suggests physiological/psychological differences between scenarios in which two people directly interact versus when they interact indirectly or simply perform related tasks. There is however a lack of sufficient quantitative data or any method to interpret that data. In addition, pilot studies of physiological data indicate that there is unlikely to be a single variable that easily solves the classification problem. Rather the solution is likely to involve a multi-dimensional solution with complicated dynamics. The goal of this seed project is to determine how best to collect empirical data that can be harnessed by AI approaches to solve the classification problem.
