Engineering Emergent Ecologies of Interacting Artefacts

Engineering Emergent Ecologies of Interacting Artefacts

Ioannis D. Zaharakis (Computer Technology Institute, Greece) and Achilles D. Kameas (Computer Technology Institute, Greece and Hellenic Open University, Greece)
DOI: 10.4018/978-1-59904-871-0.ch023
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Nowadays, our living environments already provide ubiquitous network connectivity and are populated by an increasing number of artefacts (objects enhanced with sensing, computation, and networking abilities). In addition, people are increasingly using mobile devices as intermediaries between themselves and the artefacts. In order to create, manage, communicate with, and reason about ubiquitous computing environments that involve hundreds of interacting artefacts and cooperating mobile devices, we propose to embed, in these entities, social memory, enhanced context memory, and shared experiences. In this context, we describe an engineering approach and a framework to deal with emergent ecologies of locally interacting artefacts that provide services not existing initially in the individuals, and exhibiting them in a consistent and fault-tolerant way. Because they are emergent, their structure or availability are not predefined or known before hand; we draw from swarm intelligence methods to describe such ecologies.

Key Terms in this Chapter

Ambient Intelligence: A set of [emergent] properties of an environment that we are in the process of creating; it is more an imagined concept than a set of specified requirements (IST Advisor Group, “Ambient intelligence: From vision to reality.” Retrieved on September 16, 2006, from In particular, AmI puts the emphasis on user friendliness, efficient and distributed services support, user empowerment, and support for human interactions. This vision assumes a shift away from PCs to a variety of devices that are unobtrusively embedded in our environment, and that are accessed via intelligent interfaces (Retrieved on September 16, 2006, from

Social Intelligence: “The ability to understand and manage men and women, boys and girls—to act wisely in human relations.” (Thorndike, 1920). According to a broader definition, social intelligence is “… a person’s ability to get along with people in general, social technique or ease in society, knowledge of social matters, susceptibility to stimuli from other members of a group, as well as insight into the temporary moods of underlying personality traits of strangers” (Vernon, 1933).

Ambient Sphere: Ecology of artificial entities coexisting unobtrusively with humans and performing collaborative tasks through a continuous evolvable process concerning both their physical and social cognitive growth.

Swarm Intelligence: “… an alternative way of designing intelligent systems, in which autonomy, emergence and distributed functioning replace control, preprogramming, and centralisation” (Bonabeau et al., 1999).

Ubiquitous Computing: “…the method of enhancing computer use by making many computers available throughout the physical environment, but making them effectively invisible to the user” (Weiser, 1993).

Plug-Synapse Model: A conceptual abstraction that enables uniform access to eGadget services/capabilities/properties and allows users to compose applications that realize a collective behaviour in a high-level programming manner (Mavrommati & Kameas, 2004)

Ambient System: A distributed platform that supports the instantiation of ambient spheres.

Hyper Objects (eGadgets): Ordinary objects that are commonly used for everyday, even mundane tasks (objects such as tables, chairs, cups, shelves, lights, carpets, etc..), and which in the future, can be enhanced with communication, processing, and sometimes sensing abilities (Mavrommati & Kameas, 2003).

Basic Building Block: Modelling abstraction representing self-sustained entities that are members of an AmI sphere.

Basic Behaviours: Predefined functions of the artefacts that are either enabled as reactions to external events or are continuously pursued to be fulfilled.

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