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George E. Mobus is Associate Professor Emeritus of Computer Science & Systems and Computer Engineering & Systems in the School of Engineering and Technology at the University of Washington Tacoma. 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 (under National Science Foundation Grant No. IIS-9907102), involved developing autonomous robot agents by emulating natural intelligence as opposed to using some form of artificial intelligence. Mobus was awarded US Patent: #5,504,839, "Processor and Processing Element for Use in a Neural Network". 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 and in numerous papers. 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.
Before completing his academic pursuits of a Ph.D., he had risen through the ranks of a small controls engineering company in Southern California, from software engineer to the top spot. The credit for success goes to the education he got in systems sciences during his MBA program and helping reshape many of the internals of the company that improved profitability and work conditions.
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
Erscheinungsjahr: | 2022 |
---|---|
Fachbereich: | Theoretische Physik |
Genre: | Physik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: |
xxi
814 S. 18 s/w Illustr. 156 farbige Illustr. 814 p. 174 illus. 156 illus. in color. |
ISBN-13: | 9783030934811 |
ISBN-10: | 3030934810 |
Sprache: | Englisch |
Ausstattung / Beilage: | HC runder Rücken kaschiert |
Einband: | Gebunden |
Autor: | Mobus, George E. |
Auflage: | 1st ed. 2022 |
Hersteller: |
Springer International Publishing
Springer International Publishing AG |
Maße: | 241 x 160 x 50 mm |
Von/Mit: | George E. Mobus |
Erscheinungsdatum: | 10.03.2022 |
Gewicht: | 1,402 kg |
George E. Mobus is Associate Professor Emeritus of Computer Science & Systems and Computer Engineering & Systems in the School of Engineering and Technology at the University of Washington Tacoma. 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 (under National Science Foundation Grant No. IIS-9907102), involved developing autonomous robot agents by emulating natural intelligence as opposed to using some form of artificial intelligence. Mobus was awarded US Patent: #5,504,839, "Processor and Processing Element for Use in a Neural Network". 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 and in numerous papers. 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.
Before completing his academic pursuits of a Ph.D., he had risen through the ranks of a small controls engineering company in Southern California, from software engineer to the top spot. The credit for success goes to the education he got in systems sciences during his MBA program and helping reshape many of the internals of the company that improved profitability and work conditions.
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
Erscheinungsjahr: | 2022 |
---|---|
Fachbereich: | Theoretische Physik |
Genre: | Physik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: |
xxi
814 S. 18 s/w Illustr. 156 farbige Illustr. 814 p. 174 illus. 156 illus. in color. |
ISBN-13: | 9783030934811 |
ISBN-10: | 3030934810 |
Sprache: | Englisch |
Ausstattung / Beilage: | HC runder Rücken kaschiert |
Einband: | Gebunden |
Autor: | Mobus, George E. |
Auflage: | 1st ed. 2022 |
Hersteller: |
Springer International Publishing
Springer International Publishing AG |
Maße: | 241 x 160 x 50 mm |
Von/Mit: | George E. Mobus |
Erscheinungsdatum: | 10.03.2022 |
Gewicht: | 1,402 kg |