Hideyuki Nakashima – författare

Our homes anticipate when we want to wake up. Our computers predict what music we want to buy. Our cars adapt to the way we drive. In today’s world, even washing machines, rice cookers and toys have the capability of autonomous decision-making. As we grow accustomed to computing power embedded in our surroundings, it becomes clear that these ‘smart environments’, with a number of devices controlled by a coordinating system capable of ‘ambient intelligence’, will play an ever larger role in our lives. This handbook provides readers with comprehensive, up-to-date coverage in what is a key technological field. . Systematically dealing with each aspect of ambient intelligence and smart environments, the text covers everything, from visual information capture and human/computer interaction to multi-agent systems, network use of sensor data, and building more rationality into artificial systems. The book also details a wide range of applications, examines case studies of recent major projects from around the world, and analyzes both the likely impact of the technology on our lives, and its ethical implications.With a wide variety of separate disciplines all conducting research relevant to this field, this handbook encourages collaboration between disparate researchers by setting out the fundamental concepts from each area that are relevant to ambient intelligence and smart environments, providing a fertile soil in which ground-breaking new work candevelop.

In the era of ubiquitous computing and networking, millions of electronic devices with computing facilities in the public space are connected with each other in ad hoc ways, but are required to behave coherently. Massively multi-agent systems, MMAS can be a major design paradigm or an implementation method for ubiquitous computing and ambient intelligence. As the infrastructure of massively multi-agent systems, technologies such as grid computing together with semantic annotation can be combined with agent technology. A new system design approach, society-centered design, may be realized by embedding participatory technologies in human society.This book originates from the First International Workshop on Massively Multi-Agent Systems, MMAS 2004, held in Kyoto, Japan in December 2004. The 25 revised full selected and invited papers give an excellent introduction and overview on massively multi-agent systems. The papers are organized in parts on massively multi-agent technology, teams and organization, ubiquitous computing and ambient intelligence, and massively multi-agent systems in the public space.

This book is a collection of papers presented at UCS 2004, held on November 8–9 in Tokyo. UCS is a series of international symposia sponsored by the special interest group Ubiquitous Computing Systems of the Information Processing Society of Japan. The ?rst UCS was held on November 17, 2003 in Kyoto. It was held as an invitation-based symposium. UCS 2004 was the second of the series, and the ?rst submission-based conference. UCS focuses on the emerging researcharea of ubiquitous computing systems. This emergence is an outcome of the rapid evolution in smart appliances and devices, as well as tremendous advances in wireless networks and mobile c- puting.Inthelastfewyears,variousapplicationsofinformationtechnologyhave been changing our everyday life rapidly and to a large extent. The best ex- ple is the use of mobile phones. By getting new sensing devices, cameras, their application ?eld is no longer limited to communication but covers data c- munications including Internet access, and data and program up-/downloading, and so on. The symposium o?ered the opportunity for in-depth exploration of the most recent research and development ?ndings in the ?eld of ubiquitous computing. The submitted papers presented at UCS 2004 suggest such a direction to future technologies, including mobile ad hoc networks, sensor networks and conte- aware technologies.

This book constitutes the refereed proceedings of the Second Pacific Rim International Workshop on Multi-Agents, PRIMA'99, held in Kyoto, Japan in December 1999. The 17 revised full papers presented were carefully reviewed and selected from a total of 43 submissions. The papers are organized in sections on agent cooperation, agent mobility, learning in multiagent systems, interface agents, and agent system design.

The study of intelligence emerged from interactions among agents has been popular. In this study it is recognized that a network structure of the agents plays an important role. The current state-of-the art in agent-based modeling tends to be a mass of agents that have a series of states that they can express as a result of the network structure in which they are embedded. Agent interactions of all kinds are usually structured with complex networks. The idea of combining multi-agent systems and complex networks is also particularly rich and fresh to foster the research on the study of very large-scale multi-agent systems. Yet our tools to model, understand, and predict dynamic agent interactions and their behavior on complex networks have lagged far behind. Even recent progress in network modeling has not yet offered us any capability to model dynamic processes among agents who interact at all scales on complex networks. This book is based on communications given at the Workshop on Emergent Intelligence of Networked Agents (WEIN 06) at the Fifth International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2006), which was held at Future University, Hakodate, Japan, from May 8 to 12, 2006. WEIN 06 was especially intended to increase the awareness of researchers in these two fields sharing the common view on combining agent-based modeling and complex networks in order to develop insight and foster predictive methodologies in studying emergent intelligenceon of networked agents. From the broad spectrum of activities, leading experts presented important paper and numerous practical problems appear throughout this book. The papers contained in this book are concerned with emergence of intelligent behaviors over networked agents and fostering the formation of an active multi-disciplinary community on multi-agent systems and complex networks.

The study of intelligence emerged from interactions among agents has been popular. In this study it is recognized that a network structure of the agents plays an important role. The current state-of-the art in agent-based modeling tends to be a mass of agents that have a series of states that they can express as a result of the network structure in which they are embedded. Agent interactions of all kinds are usually structured with complex networks. The idea of combining multi-agent systems and complex networks is also particularly rich and fresh to foster the research on the study of very large-scale multi-agent systems. Yet our tools to model, understand, and predict dynamic agent interactions and their behavior on complex networks have lagged far behind. Even recent progress in network modeling has not yet offered us any capability to model dynamic processes among agents who interact at all scales on complex networks. This book is based on communications given at the Workshop on Emergent Intelligence of Networked Agents (WEIN 06) at the Fifth International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2006), which was held at Future University, Hakodate, Japan, from May 8 to 12, 2006. WEIN 06 was especially intended to increase the awareness of researchers in these two fields sharing the common view on combining agent-based modeling and complex networks in order to develop insight and foster predictive methodologies in studying emergent intelligenceon of networked agents. From the broad spectrum of activities, leading experts presented important paper and numerous practical problems appear throughout this book. The papers contained in this book are concerned with emergence of intelligent behaviors over networked agents and fostering the formation of an active multi-disciplinary community on multi-agent systems and complex networks.