George E. Mobus
Computing and Software
Institute of Technology,
University of Washington, Tacoma
Tacoma, WA 98402
Office: (253) 692-5894, Department: (253) 692-5860, Fax: (253) 692-4424,
|| email: email@example.com || Home page: http://faculty.washington.edu/gmobus/ ||
- Ph.D. Computer Science,
University of North Texas, 1994
- M.B.A. Information Systems
and Management Science, San Diego State University, 1983
- B.A. Zoology, University
of Washington, 1973
- Upsilon Pi Epsilon Honor society member
- Associate Professor, Computing and Software Systems Program, University of Washington, Tacoma, 2001 to present.
- Assistant Professor, Dept.
of Computer Science,
Western Washington University, 1998 to 2001.
- Interim Director, Internet Studies
Center, Western Washington University, 1999 to present.
- Visiting Assistant
Dept. of Computer Science, Western Washington University, 1995 to 1998.
- Research Scientist and
Adjunct Assistant Professor, Dept. of Computer Science, Western Washington
University, 1994 to 1995.
- Lecturer, Dept. of Computer
Science, University of North Texas, 1989 to 1994
- Associate, Center for Research
in Parallel and Distributed Computing, University of North Texas, 1990
- Vice President, R & D, Chandas Corporation, Escondido, CA, 1987 to 1989.
- Executive Vice
President & General Manager, Technetics, Inc., El
Cajon, CA, 1983 to 1987.
Introduction to Computer Science, Systems Software, Data
Structures, Data Communications and Internetworking, Algorithms Analysis,
Systems Architecture, Mobile Autonomous Robotics
Pattern Recognition, Neural Networks, Survey of Computing
Problems in Internetworking, Autonomous Internet Agents, Mobile Autonomous
Robotics, Applied Distributed Computing, Seminar in Computer Science
- Named Mentor for
1998-99 Outstanding Graduate, Jennifer Gregor (WWU)
- Voted Outstanding
Faculty, 1999-00, by the Student Chapter of the Association for
Computing Machinery (ACM - WWU)
- Curriculum Development
- CS1 & 2
- Practicum in Computer
- Computer Architecture
- Internet Studies
- Software Engineering
- Behavior-based Robotics
(using Lego's Mindstorm kits)
- Embedded Systems
design and implementation
- Undergraduate Research
- NSF RUI IIS-9907102 Foraging
Search in a Mobile Robot, supporting four undergraduate research
- Independent Studies: Personal
Web Search Agent, three students
- Outreach and
- Organized a
departmental Industry Board of Advisors (WWU)
organization of the Internet Studies Center (WWU) with half of the
funding from non-state sources
- Coordinated receipts
of scholarship funds from various companies
- Coordinated alumni
- Coordinated alumni
- Conduct a Programming
Clinic for beginning programmers in CS
My research in this arena involves the
development of a biophysical computer model of something I call an abstract
economy. The main feature of the model is that it deals very explicitly with
the physics of extracting energy from a fixed, finite reserve of fuel and the
increasing energy cost of doing so. The EROEI associated with oil production
has been in steady decline for the past one hundred years due to the
increasing costs associated with finding and pumping more oil from exotic
(e.g. continental shelves) locations. Far more energy is used up producing the
infrastructure for obtaining this harder to reach oil. Today, for every BTU
of oil that is obtained from these locations, we use up 1/20th of a BTU of
previously pumped oil. Oil pumped from shallow wells in Pennsylvania or West
Texas, nearly 100 years ago only required about 1/100th of a BTU for each BTU
Systems science is the collection of highly
interrelated subjects that taken together form a kind of meta-science, or a
general science of science! Systems science includes subjects such as
cybernetics, information theory, complexity theory, the universal theory of
evolution (including sub-topics like emergence), network theory, and many
more. What is unique about systems science is that its concepts broadly apply
to every other science discipline. Indeed, many of the traditional
disciplines have developed sub-branches named "systems ...", where
the ellipsis can be filled in with names like 'biology', 'sociology',
'psychology', 'ecology', etc.
I am currently co-authoring an introductory book
on Systems Science to be published by Springer sometime next year.
Over the last few years I have rekindled one of
my first loves in science — neurobiology — to explore the nature of real
intelligence. This follows naturally from my work on autonomous agents
(below) but has led me into a rather interesting realm that would not be
obvious to those who have come to cognitive science strictly from the field
of artificial intelligence.
The Search for Sapience — The Cognitive Basis
Many disciplines are converging on the workings
of the human mind. From psychology we continue to refine probes of behavior
and decision making/problem solving. From neurobiology, especially with the
advent of dynamic imaging techniques, we have begun to map control functions
to specific areas of the brain. And from Evo-Devo
(evolution and development taken together) we are beginning to understand how
the modern human brain came into existence and how it helped Homo sapiens
emerge as the dominant hominid as well as a symbol manipulating (language and
signs) sentience. These are extraordinarily exciting times in brain research.
Neurobiologists are determining the capabilities
of the prefrontal cortex in its role of providing so-called executive
functions in guiding the reasoning and problem solving abilities of the mind.
Recently attention has turned to the prefrontal cortex, particularly the
extreme pole patch of tissue (right behind the eyes!) in processing judgment.
My interest is in determining if this processing, which I have labeled
sapience in order to distinguish the cognitive aspect from the performance
and knowledge-base aspects of wisdom, is, indeed, the basis of what we
recognize as wisdom.
- Real-time, on-line,
life-time learning algorithms.
This work has led to the development of a
learning algorithm that provides a solution to the destructive
interference problem in life-long learning systems. A patent for the
Adaptrode mechanism has been issued. The work was funded, in part, by
Caterpillar, Inc. and the patent is held jointly with that company.
- Autonomous agents in
dynamic, nonstationary environments.
I have been investigating the application of the
above learning algorithm to improve the search performance of agents in
highly dynamic and indeterminate environments. The research program is
investigating how agents can encode causal relations between object cues and
sought resources so that the cues can act as heuristic guides in future
searches. Both physical and software agents have been the subject of
investigations. This work has been funded, in part, by grants from
Caterpillar, IBM and Ark Interfaces, a subsidiary of Packard-Bell NEC. A
grant from the National Science Foundation is being used to extend the work
using a robot platform.
and Consulting Contracts, etc.
Data Regarding Student Participation in a Systems Course, Milgard
Center for Leadership and Social Responsibility, $1,250
Higher Education Coordinating Board, State of Washington, $250,000+, 9/99
Internet Studies Center, Microsoft ($83,000), US WEST ($50,000) and NetManage Inc. ($25,000), 9/99
Foraging Search in a Mobile Autonomous Robot, National Science
Foundation, Robotics and Human Augmentation Division, $56,000, 9/1/1999
Startup Funding, College of Arts & Sciences, Western Washington
Application of Neural Networks to the Control of Heavy Equipment,
Caterpillar, Inc., $67,000, 6/1/1990
Pattern Recognition Using Adaptrode-based Neural Networks,
Caterpillar, Inc., $13,500, 6/1/1991
Digital Signal Processing Equipment, Texas Instruments, Inc., $2,000,
Transputer Parallel Processing Equipment
and System Software, IBM, $7,500, 2/20/1994
An Adaptive, Mobile Agent, IBM, $15,000, 3/1/1994
Application of Machine Learning to Profile Link Usage Patterns, Ark
Interfaces - a subsidiary of Packard-Bell NEC., $32,000, 5/1/1996
Impact of the Internet on Securities Registered Agents, Pacific Harbor
Securities, Seattle, WA., $5,000, 9/27/1996
Feasibility of Adaptive Bookmark Management, Exodus Technologies,
Bellevue WA, $5,000, 6/1/97
Visiting Scholar, Pacific Northwest College
of Arts, Portland OR. Sept. 20-22. Seminars in energy and biophysical
economics – limits to growth. Public lecture on the same topic. Honorarium. http://cal.pnca.edu/e/467
Radio Interview, Wayne Brittenden’s
Counterpoint, Radio New Zealand National, 30 April 2013 (11:41). Discussed
the limits to growth and impact on economy, civilization, and the environment.
Scholarly Works and Patents
(2012). “The Role of Money in a Biophysical Economy”, Fourth Annual Biophysical Economics
Meeting, Burlington VT. Oct. October 26-28. Panel member.
- Mobus, G.E. (2012). “The
Evolution of Wisdom”, SCIENCE, WISDOM, AND THE FUTURE: Humanity's
Quest for a Flourishing Earth, Collins Foundation Press, Santa
Margarita, CA. pp 83-89.
- Mobus, G.E. (2010). Energy and
the Economic Outlook: The Good, the Bad, and the Ugly, Invited talk, The
Institute for the Future — Ten-year Forecast Retreat, April 26-27,
2010, Sausalito CA.
- Mobus, G.E. (2009). The Evolution
of Sapience, Past and Future, SCIENCE, WISDOM, AND THE FUTURE:
Humanity's Quest for a Flourishing Earth, June 24 — 28, San Luis
Obispo, California, Organized by the Collins Family Foundation and the
Orion Institute. [Invited talk at the conference.]
- Mobus, G.E. (2011). Net Energy
and the Economy: A Primer, The Third
International Biophysical Economics Meeting, April 15-16, 2011,
SUNY-ESF, Syracuse New York.
- Mobus, G.E. (2009). Peak Energy,
EROI, and the Economy: Modeling Contraction in the Flow of Net Energy
and Its Impact on Economic Activity, The Second International
Biophysical Economics Meeting, Oct. 2009, SUNY-ESF, Syracuse New
- Mobus, G.E. (2008). Money and
Energy, The First International
Biophysical Economics Meeting, Oct. 2008, SUNY-ESF, Syracuse New
- Mobus, G.E., (2002). Lessons
Learned from MAVRIC's Brain: An Anticipatory Artificial Agent and
Proto-consciousness, Computing Anticipatory Systems, D. Dubois
(Ed.), in press. This paper is an expanded version of the invited talk
- Mobus, G.E., (2001). Lessons
Learned from MAVRIC’s Brain: An Anticipatory Artificial Agent and
Proto-consciousness, Invited Talk: 5th Intl. Conf. on Computing
Anticipatory Systems, CASYS'01, Liege, Belgium
- Mobus, G.E., (2000). Adapting Robot
Behavior to a Nonstationary Environment: A
Deeper Biologically Inspired Model of Neural Processing. Accepted for
presentation: International Society for Optical Engineering,
Photonics East, Sensor Fusion and Decentralized Control in Robotic
Systems III, Boston, MA. [Refereed]
- Mobus, G.E. and Fisher, P.,
(2000). Edge-of-chaos search. In D.S. Levine, V. Brown and V.S. Shirey (Eds.), Oscillations in Neural Systems,
Chapter 16, pp 309-325, Lawrence Erlbaum Associates, Publishers.
- Mobus, G.E., (2000). Foraging
Search: Prototypical Intelligence, in Computing Anticipatory Systems,
D. Dubois (Ed.), American Institute of Physics 517, pp
- Mobus, G.E., (1999). Foraging
Search: Prototypical Intelligence, Invited Talk: 3rd Intl. Conf. on
Computing Anticipatory Systems, Liege, Belgium, [selected as Best Paper
for the Symposium].
- Mobus, G.E. and Caterpillar,
Inc., (1995). A patent, #5,504,839, "Processor and Processing
Element for Use in a Neural Network", has been awarded for the
Adaptrode leaning mechanism and a neuromimic
processor in which it is used.
- Mobus, G.E., (1994). Toward a
theory of learning and representing causal inference in neural networks.
In Neural Networks for Knowledge Representation and Inference,
D.S. Levine and M. Aparicio (Eds.), Lawrence
Erlbaum Associates, Publishers.
- Mobus, G.E., (1994). A
multi-time scale learning mechanism for neuromimic
processing. Ph.D. Dissertation (unpublished), University of North
Texas, Denton, TX.
- Mobus, G.E. and Aparicio, M. (1994). Foraging agents. In Proc.
Center for Advanced Systems Conf., IBM Toronto Laboratory, Toronto,
- Mobus, G.E. and Fisher, P.
(1994). MAVRIC's Brain. In Proc. Seventh Intl. Conf. on Industrial
& Engineering Applications of Artificial Intelligence & Expert
Systems, Austin, TX. [Refereed]
- Mobus, G.E. and Fisher, P.
(1991). Conditioned response training of robots using adaptrode-based
neural networks. In Proc. Intl. Joint Conf. on Neural Networks,
IEEE & Intl. Neural Networks Society, Seattle, WA. [Refereed]
- Mobus, G.E. and Fisher, P.
(1991). Conditioned response training for robot control: I - Continuous
adaptive learning. In AMSE Proc. Intl. Conf. on Neural Neworks., San Diego, CA.
- Mobus, G.E. and Fisher, P.
(1991). Conditioned response training for robot control: II - Simulation
results. In AMSE Proc. Intl. Conf. on Neural Neworks., San Diego, CA.
- Mobus, G.E. and Fisher, P. (1990).
The adaptrode neuristor: a spatio-temporal memory encoding mechanism for neurocomputing. Techical
Report CRPDC-90-5, University of North Texas, Dept. of Computer Science,
- Mobus, G.E. (1990). The adpatrode learning model: applications in neural
network computing. Techical Report
CRPDC-90-6, University of North Texas, Dept. of Computer Science,
- Mobus, G.E. (1983). A
cybernetic model for use in the development of formal information
systems. Master's Thesis (unpublished), San Diego State University,
San Diego, CA.
- Mobus, G.E. (1982). The
hierarchical control model basis for structured analysis. In, Proc.
Joint National Meeting, ORSA and IMS., San Diego, CA. [Refereed]
- Mobus, G.E. (1981). Harvesting
the sun's energy. Byte.
Work in Progress
- Mobus, George, Kalton, Michael (book
in progress). An Introduction to the Fundamentals of Systems Science,
Springer, NY (under contract, estimated publication in 2014).
Personal Blog: Question Everything
Opinions expressed in this blog are my own and do not represent views
or positions held by the University of Washington.