Courses » Spatial Multiagent Systems and Aggregate Computing: New Directions for Spatial Computing 2016-2017

Spatial Multiagent Systems and Aggregate Computing: New Directions for Spatial Computing (2016-2017)


The huge availability of geographical and spatial data, along with the impulse from ubiquitous and pervasive application scenarios, has pushed the boundaries of complex system engineering towards spatial computing. There, space (in any of the many possible acceptations of the term) represents at the same time the physical container of distributed pervasive applications, the source of a huge amount of data, information, and knowledge, and the target of both epistemic and practical actions.

Agents – as the basic abstraction for distributed computing –, rational agents – as the basic units for encapsulating intelligence –, and multi-agent systems (MAS) – as the social abstraction for collective behaviours – represent the most likely candidates for providing an original framework for spatial computing coherently covering conceptual, technical, and methodological issues. Accordingly, in the first part of this course we elaborate on the state-of-the art of spatial computing, and show how the classical ontological foundation for MAS (agents, societies, and environment) can coherently capture the essential aspects of spatial computing, also providing for original perspectives and research directions in the novel field of "Spatial MAS". (Slides)

In the second part, we focus on aggregate computing, a computational framework (encompassing models, languages, algorithms and platforms) for programming spatially-embedded and self-adaptive systems by focussing on the collection of devices seen as a single conceptual machine, i.e., at the aggregate level. After a short tutorial, we present recent research results connected to the engineering of resilient large-scale systems. (Slides)