Foundations and Engineering of Collective Adaptive Systems

A key observation in the "post digital revolution society" is that information and communication technologies (ICT) has become interwoven with human behaviour, the "fabric of everyday life" and social structures to such an extent, that the separating view of a "physical world" being connected with a "digital world" is ceasing. Today we talk about one "cyber-physical" world (Cyber-Physical Systems, an NSF program developed by Helen Gill in 2007), referring to a tight entanglements of real world physical objects (things, appliances) and processes (services), with their digital data representation and computations in communication networks (the "cyber"). Embedded, wirelessly connected tiny compute platforms equipped with a multitude of miniaturized sensors collect data about phenomena, analyze and interpret that data in real time, reason about the recognized context, make decisions, and influence or control their environment via a multitude of actuators. Sensing, reasoning and control, thus, are tightly interconnecting the physical and digital domains of the world, with feedback loops coupling one domain to the other. They implement notions of autonomous adaptive behavior.

Taking the plenty-hood of today’s ICT platforms with their computational, sensory, reasoning, learning, actuation and wireless communication capacities (smart phones, autonomous vehicles, digital signage networks, stock exchange broker bots, wearable computers, etc.), it is not just considered possible, but already a reality that these are programmed to operate cooperatively as planet scale ensembles of collective adaptive computing system (CAS). CAS research asks questions on the potential and opportunities of turning massively deployed computing systems to a globe-spanning super-organism, i.e. compute ensembles exhibiting properties of living organisms, like e.g. "collective intelligence" on their own. Essential aspects of CAS are that they often exhibit properties typically observed in complex systems, like (i) spontaneous, dynamic network configuration, with (ii) individual nodes acting in parallel, (iii) constantly acting and reacting to what the other agents are doing, and (iv) where the control tends to be highly dispersed and decentralized. If there is to be any coherent behavior in the system, it (v) has to arise from competition and cooperation among the individual nodes, so that the overall behavior of the system is the result of a huge number of decisions made every moment by many individual entities.

Collective adaptive systems can be addressed in different respects. One of them is socio-technical systems and complex human behaviour. Acting is constant, and it is a constant reaction to the behaviour of others. Any coherent behaviour of collectives has to come from competition and cooperation. The great challenge of collective adaptive systems is to predict and explain the macro-behaviour emanating from pure micro-interactions. In our work, we address the problem of crowds in public places.


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Alois Ferscha is university professor of Computer Science, head of the Institute for Pervasive Computing and dean of the TN Faculty at JKU Linz. Since 2006, he heads the research studio - Pervasive Computing Applications. Currently he is focused on Pervasive and Ubiquitous Computing, Networked Embedded Systems, Embedded Software Systems, Wireless Communication, Multiuser Cooperation, Distributed Interaction and Distributed Interactive Simulation.

Institute for Pervasive Computing