Design Principles for the Immune System and Other Distributed Autonomous Systems is the first book to examine the inner workings of such a variety of distributed autonomous systems--from insect colonies to high level computer programs to the immune system. It offers insight into the fascinating world of these systems that emerge from the interactions of seemingly autonomous components and brings us up-to-date on the state of research in these areas. Using the immune system and certain aspects of its functions as a primary model, this book examines many of the most interesting and troubling questions posed by complex systems. How do systems choose the right set of agents to perform appropriate actions with appropriate intensities at appropriate times? How in the immune system, ant colonies and metabolic networks does the diffusion and binding of a large variety of chemicals to their receptors permit coordination of system action? What advantages drive the various systems to complexity, and by what mechanisms do the systems cope with the tendency toward unwieldiness and randomness of large complex systems?

Design Principles for the Immune System and Other Distributed Autonomous Systems is the first book to examine the inner workings of such a variety of distributed autonomous systems--from insect colonies to high level computer programs to the immune system. It offers insight into the fascinating world of these systems that emerge from the interactions of seemingly autonomous components and brings us up-to-date on the state of research in these areas. Using the immune system and certain aspects of its functions as a primary model, this book examines many of the most interesting and troubling questions posed by complex systems. How do systems choose the right set of agents to perform appropriate actions with appropriate intensities at appropriate times? How in the immune system, ant colonies and metabolic networks does the diffusion and binding of a large variety of chemicals to their receptors permit coordination of system action? What advantages drive the various systems to complexity, and by what mechanisms do the systems cope with the tendency toward unwieldiness and randomness of large complex systems?

Design Principles for the Immune System and Other Distributed Autonomous Systems is the first book to examine the inner workings of such a variety of distributed autonomous systems--from insect colonies to high level computer programs to the immune system. It offers insight into the fascinating world of these systems that emerge from the interactions of seemingly autonomous components and brings us up-to-date on the state of research in these areas. Using the immune system and certain aspects of its functions as a primary model, this book examines many of the most interesting and troubling questions posed by complex systems. How do systems choose the right set of agents to perform appropriate actions with appropriate intensities at appropriate times? How in the immune system, ant colonies and metabolic networks does the diffusion and binding of a large variety of chemicals to their receptors permit coordination of system action? What advantages drive the various systems to complexity, and by what mechanisms do the systems cope with the tendency toward unwieldiness and randomness of large complex systems?

Many human diseases arise from the malfunction of signalling components, in particular alterations of multiple components of an integrated signalling network. Experimental and computational tools to describe and quantify these changes are increasingly available, providing a wealth of data that can stimulate systematic analysis of the entire signalling network and enable prediction of disease states not easily recognizable from complex data sets. This groundbreaking book explores the structural and temporal complexity in biological signalling exemplified in neuronal, immunological, humoral and genetic signal transduction networks. With discussions between experimentalists and theoretically oriented scientists, this book takes an interdisciplinary approach that may help switch the analysis of biological signalling from descriptive to predictive science and capture the behaviour of entire systems. Explores the structural and temporal complexity in biological signalling. Represents an unusual collocation of three different areas: immunology, cell signalling and neural networks. Contains interdisciplinary discussions between experimentalists and theoretically oriented scientists, in particular those working on computer simulations.

After I came to know Jerne's network theory on the immune system, I became fascinated with the immune system as an information system. The main pro totypes for biological information systems have been the neural systems and the brain. However, the immune system is not only an interesting informa tion system but it may provide a design paradigm for artificial information systems. With such a consideration, I initiated a project titled "autonomous decentralized recognition mechanism of the immune network and its applica tion to distributed information processing" in 1990 under a Grant-in-Aid for Scientific Research on a Priority Area ("Autonomous Distributed Systems") supported by the Ministry of Education, Science, and Culture. During the project, I promoted the idea that the immune system could be a prototype of autonomous distributed systems. After the project, we organized an international workshop on immunity based systems in 1996 in conjunction with the International Conference on Multi-Agent Systems held in Kyoto, Japan. Recently, there have been several international conferences related to topics inspired by the immune system and an increasing number of research papers related to the topic. In writing this book, a decade after the project, I still believe that the immune system can be a prototype, a compact but sophisticated system that nature has shown us for building artificial information systems in this network age of the twenty-first century.

Broad perspective on collectivity in the life sciences, from microorganisms to human consensus, and the theoretical and empirical opportunities and challenges. Many researchers and scholars in the life sciences have become increasingly critical of the traditional methodological focus on the individual. This volume counters such methodological individualism by exploring recent and influential work in the life sciences that utilizes notions of collectivity, sociality, rich interactions, and emergent phenomena as essential explanatory tools to handle numerous persistent scientific questions in the life sciences. The contributors consider case studies of collectivity that range from microorganisms to human consensus, discussing theoretical and empirical challenges and the innovative methods and solutions scientists have devised. The contributors offer historical, philosophical, and biological perspectives on collectivity, and describe collective phenomena seen in insects, the immune system, communication, and human collectivity, with examples ranging from cooperative transport in the longhorn crazy ant to the evolution of autobiographical memory. They examine ways of explaining collectivity, including case studies and modeling approaches, and explore collectivity's explanatory power. They present a comprehensive look at a specific case of collectivity: the Holobiont notion (the idea of a multi-species collective, a host and diverse microorganisms) and the hologenome theory (which posits that the holobiont and its hologenome are a unit of adaption). The volume concludes with reflections on the work of the late physicist Eshel Ben-Jacob, pioneer in the study of collective phenomena in living systems. Contributors Oren Bader, John Beatty, Dinah R. Davison, Daniel Dor, Ofer Feinerman, Raghavendra Gadagkar, Scott F. Gilbert, Snait B. Gissis, Deborah M. Gordon, James Griesemer, Zachariah I. Grochau-Wright, Erik R. Hanschen, Eva Jablonka, Mohit Kumar Jolly, Anat Kolumbus, Ehud Lamm, Herbert Levine, Arnon Levy, Xue-Fei Li, Elisabeth A. Lloyd, Yael Lubin, Eva Maria Luef, Ehud Meron, Richard E. Michod, Samir Okasha, Simone Pika, Joan Roughgarden, Eugene Rosenberg, Ayelet Shavit, Yael Silver, Alfred I. Tauber, Ilana Zilber-Rosenberg

What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of neurons produce something as extraordinarily complex as consciousness? In this remarkably clear and companionable book, leading complex systems scientist Melanie Mitchell provides an intimate tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. Based on her work at the Santa Fe Institute and drawing on its interdisciplinary strategies, Mitchell brings clarity to the workings of complexity across a broad range of biological, technological, and social phenomena, seeking out the general principles or laws that apply to all of them. Richly illustrated, Complexity: A Guided Tour--winner of the 2010 Phi Beta Kappa Book Award in Science--offers a wide-ranging overview of the ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for its contribution to solving some of the most important scientific questions of our time.