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CHAPTER 14

Meta-Agents: Using Multi-Agent

Networks to Manage Dynamic

Changes in the Internet of Things

Hesham Fouad, Ira S. Moskowitz
Information Management & Decisions Architecture Branch, Naval Research Laboratory, Washington,
DC, United States

14.1 INTRODUCTION

The rapid growth of the Internet of Things (IoT) (Columbus, 2017) has cre-
ated fertile ground for emerging research on a variety of existing and novel
problems, such as privacy, cyber security, big data, and self-adaptation/
self-organization. A single IoT device (e.g., a thermostat) may serve a par-
ticular purpose, but the conglomeration of multiple devices to serve a
human, or a virtual entity’s global objective, is the true promise of IoT.
The vision of pervasive or ubiquitous computing is the existence of compu-
tational middleware that discovers, and utilizes, a set of IoT resources so
that they constructively cooperate with each other in order to achieve an
identified global objective.
We note that this global objective, or objective for short, can be as simple
as assisting a homemaker in the shopping and preparation of family meals,
or as complex as a dynamic medical sensor network assisting in the care
of hundreds, or thousands, of patients. An inherent challenge of IoT is that
computational entities must operate in a highly dynamic environment,
interacting with emergent phenomena that continuously change context,
and may do so in unpredictable ways. Existing software-design paradigms
cannot address many of these problems because they approach the bounds
of the complexity manageable by a human designer. Existing software par-
adigms need to be extended, and possibly new ones created, to deal with the
complexity brought about by the rise of self-organizing, adaptive, multi-
agent systems (MAS, Bernon, Chevrier, Hilaire, et al., 2006, Bernon,
Camps, Gleizes, et al., 2004, Gardelli, Viroli, Casadei, et al., 2006, Gleizes,
Camps, George, et al., 2007).

Artificial Intelligence for the Internet of Everything Copyright © 2019 Elsevier Inc.
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