Developing pervasive multi-agent systems with nature-inspired coordination

Abstract

Pervasive computing systems can be modeled effectively as populations of interacting autonomous components. The key challenge to realizing such models is in getting separately-specified and -developed sub-systems to discover and interoperate with each other in an open and extensible way, supported by appropriate middleware services. In this paper, we argue that nature-inspired coordination models offer a promising way of addressing this challenge. We first frame the various dimensions along which nature-inspired coordination models can be defined, and survey the most relevant proposals in the area. We describe the nature-inspired coordination model developed within the SAPERE project as a synthesis of existing approaches, and show how it can effectively support the multifold requirements of modern and emerging pervasive services. We conclude by identifying what we think are the open research challenges in this area, and identify some research directions that we believe are promising.

Implementing Virtual Pheromones in BDI Robots Using MQTT and Jason (Short Paper)

“…This mechanism is widely used in pervasive computing domains, ranging from indoor localisation [11], to ambient assisted living [12] and general sensor network scenarios [13].…”

Spatial awareness in pervasive ecosystems

“…It is the spatial configuration of the pedestrian, the bus stop and the bus which controls the token generation and stop requests. Zambonelli et al [2015] adopt a biochemical approach where spatial computations are structured in terms of chemical-resembling reactions, each occurring in the precise physical point where the space is located, namely, where the device is deployed. They describe a coordination model that is equipped with space-time computing mechanisms, including reification of spacetime information and a relocation service for annotations .…”

“…Situation awareness enters the picture of spatial computing precisely when the situation of interest becomes tightly dependent on (mutual) position of computations/data/events present in the network, and when actions to accordingly take are again expressed in terms of spatial computations. Various approaches surveyed by Beal et al [2013] mostly depend on the language used to describe the spatial computation: functional approaches like Proto [Beal and Bachrach, 2006], rule-based like MGS [Giavitto and Spicher, 2008] and SAPERE [Zambonelli et al, 2015], Java-based like Tota [Mamei and Zambonelli, 2008], and others featuring logic programming and process algebraic ones. A uniform way to view at how they work is to consider the paradigmatic case of the gradient data structure described in the previous section, generalise over it, and consider the notion of computational field as a first-class one.…”

Space–time programming

“…These languages do this by by providing abstractions that implicitly handle other system details such as local communication protocols. Prototypical examples include NetLogo [5], Hood [27], TOTA [28], Gro [14], MPI [29] and SAPERE [30]. -General purpose spatial languages aim to provide domain-general methods for aggregate programming of space-time computations.…”