George E. Mobus is an Associate Professor of Computer Science & Systems and Computer Engineering & Systems in the Institute of Technology at the University of Washington Tacoma. In addition to teaching computer science and engineering courses, he teaches courses in systems science to a broad array of students from across the campus. He received his PhD in computer science from the University of North Texas in 1994. His dissertation, and subsequent research program at Western Washington University, involved developing autonomous robot agents by emulating natural intelligence as opposed to using some form of artificial intelligence. He is reviving this research agenda now that hardware elements have caught up with the processing requirements for simulating real biological neurons. He also received an MBA from San Diego State University in 1983, doing a thesis on the modeling of decision support systems based on the hierarchical cybernetic principles presented in this volume. Hedid this while actually managing an embedded systems manufacturing and engineering company in Southern California. His baccalaureate degree was earned at the University of Washington (Seattle) in 1973, in zoology. He studied the energetics of living systems and the interplay between information, evolution, and complexity. By using some control algorithms that he had developed in both his undergraduate and MBA degrees in programming embedded control systems he solved some interesting problems that led to promotion from a software engineer (without a degree) to the top spot in the company.

Michael C. Kalton is Professor Emeritus of Interdisciplinary Arts and Sciences at the University of Washington Tacoma. He came to systems science through the study of how cultures arise from and reinforce different ways of thinking about and interacting with the world. After receiving a Bachelor's degree in Philosophy and Letters, a Master's degree in Greek, and a Licentiate in Philosophy from St. Louis University, he went to Harvard University where in 1977 he received a joint Ph.D. degree in East Asian Languages and Civilizations, and Comparative Religion. He has done extensive research and publication on the Neo-Confucian tradition, the dominant intellectual and spiritual tradition throughout East Asia prior to the 20th century. Environmental themes of self-organizing relational interdependence and the need to fit in the patterned systemic flow of life drew his attention due to their resonance with East Asian assumptions about the world. Ecosystems joined social systems in his research and teaching, sharing a common matrix in the study of complex systems, emergence and evolution. The interdisciplinary character of his program allowed this integral expansion of his work; systems thinking became the thread of continuity in courses ranging from the world's great social, religious, and intellectual traditions to environmental ethics and the systems dynamics of contemporary society. He sees a deep and creative synergy between pre-modern Neo-Confucian thought and contemporary systems science; investigating this potential cross-fertilization is now his major research focus.

Provides principled explanations of the process for gaining understanding of complex systems

Focuses on design principles for engineers and others as well as the analysis of extant systems

Covers methods and provides examples of how to use a knowledge base to derive abstract models for computer simulation

Part I. Foundations of Systems Understanding.- Principles of Systems Science.- System Ontology.- System Language.- Fundamentals of Systems Analysis & Design.- Part II. Analysis of Systems.- The Process of Systems Analysis.- Demonstrating the Analysis of Various Kinds of Systems: How the Ontology is Universal.- Examining the Knowledgebase.- Detailed Analysis for Understanding - A Look at a Biophysical Economics System.- Part III. Modelling of a Complex System.- Generating Models from the Knowledgebase.- Testing and Verifying Models and the Knowledgebase.- Part 4. Design for Free.- Governance Systems.- Model Scenarios and the Construction of Policies.- Design Specification.