Advances in Network Complexity
August 2013, Wiley-Blackwell
Emmert-Streib, well-known pioneers in the fi eld, have edited this volume with a view to balancing classical and modern approaches to ensure broad coverage of contemporary research problems.
The book is a valuable addition to the literature and a must-have for anyone dealing with network compleaity and complexity issues.
Connections between Artificial Intelligence, Computational Complexity and the Complexity of Graphs (Ángel Garrido)
Selection Based Estimates of Complexity Unravel Some Mechanisms and Selective Pressures Underlying the Evolution of Complexity in Artificial Networks (Hervé Le Nagard, Olivier Tenaillon)
Three Types of Network Complexity Pyramid (Fang Jin-Qing, Li Yong, Liu Qiang)
Computational Complexity of Graphs (Stasys Jukna)
The Linear Complexity of a Graph (David L. Neel, Michael E. Orrison)
Kirchhoff's Matrix Tree Theorem revisited: Counting Spanning Trees with the Quantum Relative Entropy (Vittorio Giovannetti, Simone Severini)
Dimension Measure for Complex Networks (O. Shanker)
Information Based Complexity of Networks (Russell K. Standish)
Thermodynamic Depth in Undirected and Directed Networks (Francisco Escolano, Edwin R. Hancock)
Circumscribed Complexity in Ecological Networks (Robert E. Ulanowicz)
Metros as Biological Systems: Complexity in Small Real-life Networks (Sybil Derrible)
Abbe Mowshowitz studied mathematics at the University of Chicago (BA 1961), and both mathematics and computer science at the University of Michigan (PhD 1967). He has held academic positions at the University of Toronto, The University of British Columbia, Erasmus University-Rotterdam, the University of Amsterdam and has been a professor of computer science at the City College of New York and in the PhD Program in Computer Science of the City University of New York since 1984. His research interests lie in applications of graph theory to the analysis of complex networks, and in the study of virtual organization.
Frank Emmert-Streib studied physics at the University of Siegen, Germany, gaining his PhD in theoretical physics from the University of Bremen. He was a postdoctoral research associate at the Stowers Institute for Medical Research, Kansas City, USA, and a senior fellow at the University of Washington, Seattle, USA. Currently, he is Lecturer/Assistant Professor at the Queen's University Belfast, UK, at the Center for Cancer Research and Cell Biology, heading the Computational Biology and Machine Learning Lab. His research interests are in the field of computational biology, machine learning and network medicine.
“In summary, “Advances in Network Complexity” is a valuable treatise, outlining the many facets of the contemporary approaches to network complexity. It will be useful for both experts and beginners. It should be a must for any decent science library.” (MATCH Communications in Mathematical and in Computer Chemistry, 1 March 2014)
“This volume will be particularly valuable to researchers in these areas as a resource to learn about earlier threads of network analysis coming from unfamiliar fields such as computer science and pure mathematics.” (Journal of Complex Networks, 1 March 2014)
“Theory and practical applications are intertwined to give the reader a deeper appreciation of the problems and possible solutions. Network complexity is a rapidly evolving field touching on a wide range of issues from pure mathematics, physics and chemistry to industrial processes and consumer behavior. This book satisfies a pressing need for a comprehensive overview of the current state of the field.” (AMS Journal, 1 October 2013)
“Overall, a valuable addition to the literature and a must-have for anyone dealing with complex systems. The articles of this volume will not be reviewed individually.” (Zentralblatt Math, 1 September 2013)