**2. Intelligent systems**

In computer science, intelligent systems research has its roots in the natural sciences and the study of natural systems and specifically how intelligent behavior occurs. Since the 1950s, computer scientists have sought to understand the nature of intelligence by constructing artifacts that exhibited the same breadth and depth of cognition as humans and other biological entities, such as ant colonies, swarms, etc. [9]. The search for artificial intelligence (AI) is a search for systems that think like humans, think rationally, act like humans, and act rationally [10]. In this respect, AI and intelligent systems are often used synonymously. Both involve agents whose behavior is informed by inputs from their environment and take actions that

**52**

**Chapter**

**Abstract**

Everything.

**1. Introduction**

cognitive architectures, privacy

Toward the Intelligent Internet

of Everything: Observations on

Multidisciplinary Challenges in

*Theo Lynn, Pierangelo Rosati and Patricia Takado Endo*

For over 50 years, commentators have sought to envision a wired or networked

society whose social structures and activities, to a greater or lesser extent, are organized around digital information networks that connect people, processes, things, data, and networks. This phenomenon is increasingly called the Internet of Everything. Complexity is a significant concern with the Internet of Everything due to both the volume of heterogeneous entities and the nature of how such entities are related to each other and the wider environment in which they operate. Without intelligence, the Internet of Everything may not reach its full potential, hampered by predefined rules ill-suited to a changing and dynamic physical world. More recently, intelligent systems have emerged that can perceive and respond to the physical and social world around them with a greater degree of autonomy; these systems make things smart. However, such intelligent systems and smart things present both interesting and significant multilevel computational and societal research challenges, not least representing and making sense of a dynamic physical world. This chapter will introduce the Internet of Everything, present the building blocks of Intelligent Systems, and discuss some of the opportunities and challenges for multidisciplinary research in this emerging area as it relates to the Internet of

**Keywords:** intelligent systems, IOT, Internet of Things, Internet of Everything,

In their 1973 article, "The Network City," Craven & Wellman conceptualized cities as a multitude of social networks comprising systems of interaction, systems of resource allocation, and systems of integration and coordination. While at roughly the same time, the first Ethernet was invented and the first VOIP phone call was made, and the information technology is notable by its absence in "The Network City." Within 5 years, numerous researchers envisioned a "network nation" and "wired society" driven by advances in communications technology [1, 2]. Over the last four decades, the opportunities and challenges of a society mediated by technology have been a major focus of academia, policymakers, and industry expanding

Intelligent Systems Research

maximize their probability of achieving a goal [11]. However, some commentators suggest that intelligent systems are simply what it says on the tin: systems with some degree of intelligence. In this respect, some, relatively simple intelligent systems, may not be perceived to be AI. This is, most likely, a reflection of the so-called AI effect, that is, if an AI can successfully solve a problem, it is no longer part of AI [12, 13]. Kotseruba and Tsotsos [14] suggest that instead of looking for a particular definition of intelligence, it may be more practical to explore systems against the set of competencies and behaviors demonstrated by the system.
