A Distributed Ambient Intelligence Based Multi-Agent System for Alzheimer Health Care

This chapter presents ALZ-MAS (Alzheimer multi-agent system), an ambient intelligence (AmI)-based multi-agent system aimed at enhancing the assistance and health care for Alzheimer patients. The system makes use of several context-aware technologies that allow it to automatically obtain information from users and the environment in an evenly distributed way, focusing on the characteristics of ubiquity, awareness, intelligence, mobility, etc., all of which are concepts defined by AmI. ALZ-MAS makes use of a services oriented multi-agent architecture, called flexible user and services oriented multi-agent architecture, to distribute resources and enhance its performance. It is demonstrated that a SOA approach is adequate to build distributed and highly dynamic AmI-based multi-agent systems

Improving Context-Awareness in a Healthcare Multi-Agent System

Context-aware technologies allow Ambient Assisted Living systems and applications to automatically obtain information from users and their environment in a distributed and ubiquitous way. One of the most important technologies used to provide context-awareness to a system is Wireless Sensor Networks. This paper describes last improvements made on ALZ-MAS, an Ambient Intelligence based multi-agent system aimed at enhancing the assistance and healthcare for Alzheimer patients. In this sense, a new ZigBee platform is used to improve ALZ-MAS. This platform provides the system with new telemonitoring and locating engines that facilitate the integration of context-awareness into it

From Physical to Virtual: Widening the Perspective on Multi-Agent Environments

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-23850-0_9Since more than a decade, the environment is seen as a key element when analyzing, developing or deploying Multi-Agent Systems (MAS) applications. Especially, for the development of multi-agent platforms it has become a key concept, similarly to many application in the area of location-based, distributed systems. An emerging, prominent application area for MAS is related to Virtual Environments. The underlying technology has evolved in a way, that these applications have grown out of science fiction novels till research papers and even real applications. Even more, current technologies enable MAS to be key components of such virtual environments. In this paper, we widen the concept of the environment of a MAS to encompass new and mixed physical, virtual, simulated, etc. forms of environments. We analyze currently most interesting application domains based on three dimensions: the way different "realities" are mixed via the environment, the underlying natures of agents, the possible forms and sophistication of interactions. In addition to this characterization, we discuss how this widened concept of possible environments influences the support it can give for developing applications in the respective domains.Carrascosa Casamayor, C.; Klugl, F.; Ricci, A.; Boissier, O. (2015). From Physical to Virtual: Widening the Perspective on Multi-Agent Environments. En Agent Environments for Multi-Agent Systems IV. 4th International Workshop, E4MAS 2014 - 10 Years Later, Paris, France, May 6, 2014. 133-146. https://doi.org/10.1007/978-3-319-23850-0_9S133146Aggarwal, J.K., Ryoo, M.S.: Human activity analysis: a review. ACM Comput. 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Agents and Ambient Intelligence, Ambient Intelligence and Smart Environments, pp. 17–31. IOS Press, Amsterdam (2012)Ferber, J.: Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence. Addison Wesley Longman, Harlow (1999)Gelernter, D.: Mirror Worlds - or the Day Software Puts the Universe in a Shoebox: How it Will Happen and What it Will Mean. Oxford University Press, New York (1992)Gibson, W.: Neuromancer. Ace, New York (1984)Klügl, F., Fehler, M., Herrler, R.: About the role of the environment in multi-agent simulations. In: Weyns, D., Van Parunak, H.D., Michel, F. (eds.) E4MAS 2004. LNCS (LNAI), vol. 3374, pp. 127–149. Springer, Heidelberg (2005)Krueger, M.: Artificial Reality II. Addison-Wesley, New York (1991)Luck, M., Aylett, R.: Applying artificial intelligence to virtual reality: intelligent virtual environments. Appl. Artif. Intell. 14(1), 3–32 (2000)Dorigo, M., Floreano, D., Gambardella, L.M., et al.: Swarmanoid: a novel concept for the study of heterogeneous robotic swarms. IEEE Robot. Autom. Mag. 20(4), 60–71 (2013)Milgram, P., Kishino, A.F.: Taxonomy of mixed reality visual displays. IEICE Trans. Inf. Syst. E77–D(12), 1321–1329 (1994)Olsson, T., Salo, M.: Online user survey on current mobile augmented reality applications. In: Proceedings of the 2011 10th IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2011, pp. 75–84. IEEE Computer Society, Washington, DC, USA (2011)Saunier, J., Balbo, F., Pinson, S.: A formal model of communication and context awareness in multiagent systems. J. Logic Lang. Inform. 23(2), 219–247 (2014)Stephenson, N.: Snow Crash. Bantam Books, New York (1992)Tummolini, L., Castelfranchi, C.: Trace signals: the meanings of stigmergy. In: Weyns, D., Van Parunak, H.D., Michel, F. (eds.) E4MAS 2006. LNCS (LNAI), vol. 4389, pp. 141–156. Springer, Heidelberg (2007)Weyns, D., Omicini, A., Odell, J.: Environment as a first class abstraction in multiagent systems. Auton. Agent. Multi-Agent Syst. 14(1), 5–30 (2007)Weyns, D., Schelfthout, K., Holvoet, T., Lefever, T.: Decentralized control of e’gv transportation systems. In: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 67–74. ACM (2005)Weyns, D., Schumacher, M., Ricci, A., Viroli, M., Holvoet, T.: Environments in multiagent systems. Knowl. Eng. Rev. 20(2), 127–141 (2005

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications