Agent based systems have been explored, if not practically, at least conceptually, in a wide range of domains. The notion of agent has taken, also, many shapes and meanings according to the application area. These have ranged from pure computational applications, such as UNIX daemons, Internet crawlers, optimization algorithms, etc; to embodied agents as in mobile robotics. The notion of cyber-physical system has been very recently coined to denote the next generation of embedded systems. Unlike an embedded system, a cyber-physical system is designed from scratch to promote the symbiosis and fusion between a physical element, its controller, and its abstract or logical representation/existence. To an enormous extent the concept echoes the idea of embodiment (Pfeifer, Lungarella & Iida 2007), whereby the body shapes the cognitive abilities of its control gear, and self-organization (Holland & Melhuish 1999), in the sense that a resilient whole results from the collective interactions of many parts. Some rather similar principles have been the basis for Holonic Manufacturing Systems (HMS) (Bussmann & Mcfarlane 1999), Bionic Manufacturing Systems (BMS) (Ueda 1992), Evolvable Assembly Systems (EAS) (Onori 2002) and an overwhelming number of industrial agent based architectures that have followed them (Van Brussel et al. 1998; Leitao, Colombo & Restivo 2005; Barata 2003; Lastra 2004; Shen et al. 2006; Marik & Lazansky 2007; Vrba et al. 2011; Leitão 2009; Monostori, Váncza & Kumara 2006).
It is therefore safe to assert that industrial agent systems are a preceding, probably more restricted, case of cyber-physical systems.
Although each application area has its specific challenges arguably, the design, deployment and assessment of industrial agent systems are particularly complex. Given the multidisciplinary nature of today's industrial systems, their cyber-physical realization entails challenges that range from pure computer science and embedded controller design to production optimization and sustainability.
The main challenges comprising the design, deployment and assessment of industrial agent-based systems are therefore examined.
Multiagent Systems (MAS) have been widely known as the base for inherent robust and available systems and there are many characteristics (Wooldridge & Jennings 1994; Wooldridge & Jennings 1995) such as autonomy, social-ability, proactive response, reactivity, self-organization, etc; which have been identified as core ingredients for the MAS reliability.
However, to call "agent" to a software abstraction and create a system based on these abstractions is not a guarantee that the system will exhibit the expected characteristics. Unfortunately this misconception is quite common.
There have been significant international and industrial efforts in addressing the different design, deployment and assessment challenges. The reader is naturally referred to the contents of this book to learn about the latest results and technical details. Previous international projects are not limited to but include: SIRENA - early development of a devices profiles for web services (DPWS) stack (Jammes & Smit 2005; Bohn, Bobek & Golatowski 2006) and subsequent project SODA - focusing on the development of a service based ecosystem using DPWS, Inlife - focusing in service oriented diagnosis of distributed intelligent systems (Barata, Ribeiro & Colombo 2007), SOCRADES - investigating the creation of new methodologies, technologies and tools for the modelling, design, implementation and operation of networked hardware/software systems embedded in smart physical objects (De Souza et al. 2008), AESOP - tackling web service-oriented process monitoring and control (Karnouskos et al. 2010), GRACE - exploring process and quality control integration using a MAS framework (Stroppa et al. 2012) and IDEAS - focusing in instant deployment of agentified components (Ribeiro et al. 2011a).
The subsequent details are therefore organized to first highlight the commonest structural arrangements considered in current agent architectures and more specifically on bringing some context on their potential applications and limitations. Secondly, since emerging architectures are increasingly inspired by concepts and methods from the complexity sciences, the gaps between them and the concrete instantiation of industrial MAS are discussed. The presentation of the design challenges and opportunities follows as well as the conventional deployment approaches. Finally, the impact of MAS design is discussed from a system validation perspective.