As it appears in this list, complex systems
constitute an immensely vast interdisciplinary topic!
Therefore, it cannot be the intention of this seminar to be exhaustive or systematic but
rather to offer an exploration and discovery of complex systems
through "sampling" of the literature and pragmatic experiments.
This advanced-level interdisciplinary course welcomes all graduate
students in science and engineering, including: Computer Science &
Engineering, Mathematics, Physics, Electrical Engineering, Chemistry,
Biology, Biomedical Engineering, Earth Sciences, and others.
Beside lectures by the instructor, students will read and present
scientific articles (1.0 credit) and can also elect to complete
modeling & simulation programming exercises and a term research
project (3.0 credits).
Other faculty members will also be invited to give talks and
co-supervise student projects, with potential for publications.
Prerequisites: a basic mathematical background, a curious scientific
mind and, if elected, good programming skills.
- Required printed textbook
|
Camazine, S., Deneubourg, J.-L., Franks, N. R., Sneyd, J., Theraulaz, G. and Bonabeau, E. (2003)
Self-Organization in Biological Systems.
Princeton University Press (ISBN: 0691116245). |
- Required online textbooks
|
Wolfram, S. (2002) A New Kind of Science. Wolfram Media (ISBN: 1579550088).
Note: After browsing a few pages, you will be asked to register
your email for further reading. Refer to the
FAQs about NKS|Online for help. |
|
Bar-Yam, Y. (1997) Dynamics of Complex Systems. Perseus Books (ISBN: 0813341213).
Note: If the page does not appear, copy and paste the following URL
in your browser: http://necsi.org/publications/dcs
The problem seems to be caused by a server-side redirection to a
nonconventional port, which your firewall might be blocking. |
- Recommended textbooks
|
Flake, G. (1998) The Computational Beauty of Nature. MIT Press (ISBN: 0262561271). |
|
Ball, P. (1999) The Self-Made Tapestry: Pattern Formation in Nature. Oxford University Press (ISBN: 0198502435). |
This is an illustrative list of topics. It does not necessarily
follow the chronological order of the meetings and is subject to
modification and reorganization, depending on the number of
participants. Not all authors or works are cited here, while some
items cited here might not be addressed in class.
- Overview of complex systems
- Examples & principles
- NetLogo platform
- Physics & phase transitions
- spin glasses, Ising model
- Rayleigh-Bénard convection
- Cellular automata
- Conway's "Game of Life"
- Wolfram's four classes of cellular automata
- Langton's "lambda" parameter
- Excitable media: chemical and cellular traveling waves
- processes of reaction-diffusion
- chemical oscillations and the Belousov-Zhabotinsky reaction
- slime mold aggregation
- pacemaker heart waves
- wave dynamics in cortical neural networks
- Developmental biology
- Kauffman's gene networks (cellular differentiation)
- pattern formation in organism development
- Turing's morphogenesis paper (1952)
- animal coats (spots & stripes)
- butterfly wings
- sea shells (cellular automata)
- plant growth & phyllotaxis
- Social insects and swarm intelligence
- adaptive trail formation in ants
- swarm raids in army ants
- division of labor in ants
- Dorigo's "Ant Colony Optimization" (ACO)
- nest building by termites (continuous stigmergy)
- nest building by wasps (discrete stigmergy)
- comb patterns in honey bees
- Coordinated population behavior
- synchronized flashing in fireflies
- fish schooling, bird flocking, cattle herding (Reynold's "boids")
- Kennedy & Eberhardt's "Particle Swarm Optimization"
- traffic jams
- Ecosystems & economics
- elements of Game Theory
- spatially extended ecological systems
- Robert Axelrod's "Iterated Prisoner's Dilemma"
- competition & cooperation
- Kaneko & Solé's "Coupled Map Lattices"
- Jim Lovelock's "Daisy World" (homeostasis)
- multi-population dynamics, community ecology, complex webs
- Evolution & adaptation
- Kauffman's random autocatalytic networks (origins of life)
- Holland's "Genetic Algorithms"
- variants: Evolutionary Programming, Evolutionary Strategies,
Genetic Programming
- Kauffman's NK models
- rugged fitness landscapes
- coevolution
- explosions and extinctions
- Langton's "Artificial Life"
- Ray's "Tierra"
- Neural networks & cognitive science
- Hopfield's associative memory
- perceptrons
- spiking neuron models
- synchronized oscillators
- pulse coupled networks
- synfire chains
- chaotic EEG's
- Complex networks
- random networks
- "small-world" networks
- scale-free networks
- network dynamics
- spread of diseases
- food webs
- Internet & the Web
- Assignments
- Lectures & guest talks
I will give introductory lectures to complex systems, NetLogo
and other complexity topics. I will open, moderate and
conclude the students' paper presentations. There will also
be a few invited talks from other faculty members.
- Paper presentations and discussions
Students will choose journal papers and book chapters from
a reading list and prepare presentations for the class.
There will be 1 or 2 required readings per session (possibly
in combination with additional sources), to be read by
everyone and presented by 1 or 2 students. Presentations must
be prepared using Microsoft PowerPoint, contain figures and
be emailed to the instructor. Speakers should also run a
companion demo (ready-made or self-made) to illustrate the
presented topic, including an exploration of the parameters
and overview of the code. Total duration: 60 minutes,
including the demo.
- Quizzes
There may be announced and unannounced short quizzes about
the contents of the articles and concepts reviewed in class.
There will be no makeups for missed quizzes. The lowest
quiz grade(s) might be dropped at the end of the term.
- Homework assignments Students will carry
out "convince-yourself" experiments in the form of programming
exercises, generally derived from the models reviewed in class.
Some exercises will be based on the NetLogo platform, others written
in a programmation language such as C/C++, Java, Fortran,
MATLAB, etc. There will be approximately one homework
assignment every other week (every 4 sessions).
- Research project Students will also
complete a modeling & simulation project individually.
This includes a program (written in the language of their choice),
a technical report and a presentation to the class with a live demo.
Topics chosen by the students must address complex systems
and may be either related to the paper reviews, or overlapping with
their current MSc or PhD work in progress, or fully original for this seminar.
Important deadlines (see schedule below): 1 month after start =
project proposals; 2 months after start = project status reports;
end of the semester = final code, report and presentation.
- Late policy Late assignments of any kind
(presentation, exercises, project) will not be accepted.
- Academic integrity
There will be no team projects or reports in this class, therefore
all assignments and quizzes must be prepared strictly
individually. Any form of cheating such as plagiarism or
ghostwriting will incur a severe penalty, usually failure in the
course. Please refer to the UNR policy on Academic Standards.
- Disability statement
If you have a disability for which you will need to request
accommodations, please contact the instructor or someone at the
Disability Resource Center (Thompson Student Services - 107)
as soon as possible.
Credits will be based on the involvement with assignments
2, 3, 4 and 5 (see above) and attendance throughout the semester,
according to the following sliding scale:
- 1.0 credit for attendance + completion of 2 and 3
- 3.0 credits for attendance + completion of 2, 3, 4 and 5.
Grading from A to F will depend on the participation in discussions,
quality of presentations and quiz responses (2 and 3) and, if elected,
the successful completion of programming exercises and research project (4 and 5).
• Grading Policy
|
1.0 credit |
3.0 credits |
1. Attendance & participation |
20% |
10% |
2. Paper presentations |
60% |
20% |
3. Quizzes |
20% |
10% |
4. Programming exercises |
-- |
20% |
5. Research project |
-- |
40% |
|
|
• Grading Scale
90% - 100% | A-, A |
80% - 89% | B-, B, B+ |
65% - 79% | C-, C, C+ |
55% - 64% | D |
0% - 54% | F |
|
See below for references.
The NetLogo
demo scripts can be found in the /models folder of the
NetLogo installation directory.
Date |
Speaker |
Topic |
Presentation Papers |
Background References |
Presentation Demo |
Jan 23 |
|
Introduction 1 - Examples of complex systems (part I) and course organization
|
Jan 25 |
|
Introduction 2 - Examples (part II) and concepts of complex systems
|
Jan 30 |
Jirakhom Ruttanavakul |
Cellular Automata 1 -
a. Introduction
b. Types of Behaviors
|
•
•
|
-- |
• NetLogo: Life
|
Adam Olenderski |
•
|
-- |
• NetLogo: CA 1D
|
Feb 1 |
Edward Dochtermann |
Cellular Automata 2 -
a. Types of Randomness
b. Models of Nature
|
•
|
-- |
-- |
Beifang Yi |
•
|
-- |
-- |
Feb 6 |
Kyle McDermott |
Pattern Formation 1 -
Reaction-Diffusion Patterns
|
•
•
•
|
•
•
|
• NetLogo: Fur
• Texture Garden
|
Feb 8 |
Kara DeSouza |
Pattern Formation 2 -
Excitable Media Waves
|
•
•
•
|
•
|
• NetLogo: B-Z
|
Feb 13 |
Erick Luerken |
Swarm Intelligence 1 -
Particle Swarm Optimization
|
•
•
•
•
|
•
• Pomeroy (2003)
• PSO site
|
• NetLogo: Flocking
• Boids
|
Feb 15 |
Edward Dochtermann |
Swarm Intelligence 2 -
Ant Colony Optimization
|
•
•
•
|
• ACO site
|
• NetLogo: Ants
|
Feb 20 |
President's Day - no class |
Feb 22 |
|
Neural Networks 1 -
Synchronization in Neural Networks
|
Feb 27 |
Olenderski |
Project Proposal -
Robot Learning by Demonstration
|
McDermott |
Project Proposal -
Retinal Remodeling by Ant Colonies
|
Zirpe |
Project Proposal -
Neocortical Microcircuits
|
Ruttanavakul |
Project Proposal -
A Dynamic-Network Robot Controller
|
Mar 1 |
Milind Zirpe |
Neural Networks 2 -
Attractor Networks
|
•
•
|
•
|
• NetLogo: Hopfield
• Hopfield applet
|
Mar 6 |
Kara DeSouza |
Complex Networks 1 -
a. Small-World Experiments
b. Small-World Models
|
•
•
•
|
•
• Small World Project
• Big World critique
|
• NetLogo: Small World
• Small World applet
• Oracle of Bacon
|
Kyle McDermott |
Mar 8 |
Jirakhom Ruttanavakul |
Complex Networks 2 -
a. Scale-Free Networks
b. Complex Networks
|
•
•
•
|
• Complex Network Center
|
• NetLogo: Attachment
• Visual Complexity
|
|
Mar 13 |
Milind Zirpe |
Spatial Communities 1 -
a. Spatial Ecology (a)
b. Spatial Ecology (b)
|
•
•
•
|
•
|
• NetLogo: Predation
• NetLogo: Pred. docked
|
Erick Luerken |
Mar 15 |
Adam Olenderski |
Spatial Communities 2 -
Evolutionary Game Theory
|
•
•
•
|
•
|
• NetLogo: PD Two Person
• NetLogo: PD Evolutionary
|
Mar 20 |
Spring Break - no class |
Mar 22 |
Spring Break - no class |
Mar 27 |
Kara DeSouza |
Paper Review -
Conceptual Topology |
•
|
-- |
-- |
Adam Olenderski |
Paper Review -
Small-World Language |
•
|
-- |
-- |
Mar 29 |
Kyle McDermott |
Paper Review -
Mobile Social Agents |
•
|
-- |
-- |
Erick Luerken |
Paper Review -
Distance in Complex Nets |
•
|
-- |
-- |
Apr 3 |
Edward Dochtermann |
Paper Review -
Complex Food Webs |
•
|
-- |
-- |
Jirakhom Ruttanavakul |
Paper Review -
Dynamics of Complex Nets |
•
|
-- |
-- |
Apr 5 |
Milind Zirpe |
Paper Review -
Self-Organized Behavior |
•
|
-- |
-- |
Sebastian Smith
|
Paper Review -
Plant Computation
|
•
|
-- |
-- |
Apr 10 |
Olenderski |
Project Status -
Conceptual Structure of the Human Mind
|
McDermott |
Project Status -
Retinal Remodeling by Ant Colonies
|
Zirpe |
Project Status -
Neocortical Microcircuits
|
Ruttanavakul |
Project Status -
A Dynamic-Network Robot Controller
|
Apr 12 |
|
Invited Talk -
Evolution as a complex process
|
Apr 17 |
Ruttanavakul |
Artificial Life 1 -
Genetic Algorithms |
•
• |
-- |
• Introduction to GAs
• GA Viewer
|
Smith |
Apr 19 |
Dochtermann |
Artificial Life 2 -
Evolutionary Computation
|
•
|
-- |
• Avida
|
Zirpe |
Apr 24 |
DeSouza |
Order for Free 1 -
Genetic Nets
|
•
|
•
• Order for Free
• The Origin of Order
• Investigations
|
-- |
McDermott |
Apr 26 |
Luerken |
Order for Free 2 -
Autocatalytic Sets |
•
|
-- |
Olenderski |
May 1 |
|
Invited Talk -
Computational Universality
|
•
•
|
-- |
-- |
May 3 |
ALL
|
Self-Organization 1
|
• |
-- |
-- |
May 8 |
ALL
|
Self-Organization 2
|
• |
-- |
-- |
May 10 |
Prep Day - no class |
May 11 |
Olenderski |
Project Final -
Conceptual Structure of the Human Mind
|
McDermott |
Project Final -
Retinal Remodeling by Ant Colonies
|
Zirpe |
Project Final -
Neocortical Microcircuits
|
Ruttanavakul |
Project Final -
A Dynamic-Network Robot Controller
|
See below for references.
Start Date |
Due Date |
Assignment |
References |
Jan 23 |
Jan 30, 2:30pm |
• Install and play with NetLogo on your computer
|
• NetLogo
|
Feb 13 |
Feb 22, 2:30pm |
• Written Assignment 1
• Written Assignment 2
|
-- |
Feb 22 |
Mar 1, 2:30pm |
• Written Assignment 3
|
-- |
Mar 15 |
Mar 29, 2:30pm |
• Written Assignment 4
|
-- |
References will be continuously added as the seminar unfolds.
Please check again regularly.
Articles with online text are indicated with a direct link to the text
or a link to the journal via the UNR Library subscription (you will need
your library code outside of the university network).
Books links refer either to the full text, a third-party review of the book
or a presentation Web site that may include useful information and material
such as table of contents, illustrations, selected chapters, companion software,
etc.
Disclaimer: third-party Web sites offering online contents or reviews are
not considered course material in their entirety, only the
specific links presented here.
- Axelrod, R. and Hamilton, W. D. (1981)
The evolution of cooperation.
Science, 211(4489): 1390-1396.
- Ball, P. (1999)
The Self-Made Tapestry: Pattern Formation in Nature.
Oxford University Press.
- Barabási, A.-L. and Albert, R. (1999)
Emergence of scaling in random networks.
Science, 286(5439): 509-512.
- Barabási, A.-L. and Bonabeau, E. (2003)
Scale-free networks [9.3MB].
Scientific American, 288: 60-69.
- Barabási, A.-L., Dezsö, Z., Ravasz, E., Yook, S. H. and Oltvai, Z. (2002)
Scale-free and hierarchical structures in complex networks.
Proceedings of the XVIII Sitges Conference on Statistical Mechanics of Complex Networks,
Springer-Verlag.
- Bar-Yam, Y. (1997)
Dynamics of Complex Systems.
Perseus Books.
- Bascompte, J. and Solé, R. V. (1995)
Rethinking complexity: modelling spatiotemporal dynamics in ecology.
Trends in Ecology and Evolution, 10(9): 361-366.
- Brady, A. H. (1988)
The Busy Beaver game and the meaning of life.
In The Universal Turing Machine: A Half-Century Survey,
R. Herken, ed., pp. 259-277. Oxford University Press.
- Camazine, S., Deneubourg, J.-L., Franks, N. R.,
Sneyd, J., Theraulaz, G. and Bonabeau, E. (2003)
Self-Organization in Biological Systems.
Princeton University Press.
- Dewdney, A. K. (1988)
The hodgepodge machine makes waves.
Scientific American, 259(2): 104-107.
- Dorigo, M., and Gambardella, L. M. (1997)
Ant colonies for the traveling salesman problem.
Biosystems, 43: 73-81.
- Dorigo, M., Maniezzo, V. and Colorni, A. (1996)
The ant system: optimization by a colony of cooperating agents.
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics,
26(1): 29-41.
- Ferrer-i-Cancho, R. and Solé, R. V. (2001)
The small world of human language.
Proc. R. Soc. Lond. B, 268(1482): 2261-2265.
- Flake, G. (1998)
The Computational Beauty of Nature.
MIT Press.
- Gardner, M. (1970)
Mathematical Games: The fantastic combinations of
John Conway's new solitaire game "life".
Scientific American, 223(4): 120-123.
- Gerhardt, M. and Schuster, H. (1989)
A cellular automaton describing the formation of spatially ordered
structures in chemical systems.
Physica D: Nonlinear Phenomena, 36(3): 209-221.
- Goldberg, D. E. (1989)
Genetic Algorithms in Search, Optimization and Machine Learning.
Addison-Wesley.
- González, M. C., Lind, P. G. and Herrmann, H. J. (2006)
System of mobile agents to model social networks.
Physical Review Letters, 96: 088702.
- Gorman, S. P., Schintler, L., Kulkarni, R. and Stough, R. (2004)
The revenge of distance: vulnerability analysis of critical information infrastructure.
J. Contingencies and Crisis Management, 12(2): 48-63.
- Hassell, M. P., Comins, H. N. and May, R. M. (1991)
Spatial structure and chaos in insect population dynamics.
Nature, 353(6341): 255-258.
- Hopfield, J. J. (1982)
Neural networks and physical systems with emergent collective computational abilities.
Proc. Natl. Acad. Sci. USA, 79(8): 2554-2558.
- Huth, A. and Wissel, C. (1992)
The simulation of the movement of fish schools.
Journal of Theoretical Biology, 156: 365-385.
- Kauffman, S. A. (1969)
Metabolic stability and epigenesis in randomly constructed genetic nets.
Journal of Theoretical Biology, 22: 437-467.
- Kauffman, S. A. (1986)
Autocatalytic sets of proteins.
Journal of Theoretical Biology, 119: 1-24.
- Kauffman, S. A. (1995)
At Home in the Universe: The Search for the Laws of Self-Organization and Complexity.
Oxford University Press.
- Kennedy, J. and Eberhart, R. C. (1995)
Particle swarm optimization.
In Proceedings of the IEEE 1995 International Conference on Neural Networks, pp. 1942-1948.
- Kennedy, J. and Eberhart, R. C. (1997)
A discrete binary version of the particle swarm algorithm.
In Proceedings of the IEEE 1997 International Conference on Systems, Man and Cybernetics, pp. 4104-4109.
- Lenski, R. E., Ofria, C., Pennock, R. T. and Adami, C. (2003)
The evolutionary origin of complex features.
Nature, 423: 139-144.
- Millor, J., Pham-Delegue, M., Deneubourg, J. L. and Camazine, S. (1999)
Self-organized defensive behavior in honeybees.
Proc. Natl. Acad. Sci. USA, 96(22): 12611-12615.
- Motter, A. E., de Moura, A. P. S., Lai, Y.-C. and Dasgupta, P. (2002)
Topology of the conceptual network of language.
Physical Review E, 65: 065102.
- Nowak, M. A. and May, R. M. (1992)
Evolutionary games and spatial chaos.
Nature, 359(6398): 826-829.
- Peak, D., West, J. D., Messinger, S. M. and Mott, K. A. (2004)
Evidence for complex, collective dynamics and
emergent, distributed computation in plants
Proc. Natl. Acad. Sci. USA, 101(4): 918-922.
- Pearson, J. E. (1993)
Complex patterns in a simple system.
Science, 261(5118): 189-192.
- Reynolds, C. W. (1987)
Flocks, herds and schools: a distributed behavioral model.
Computer Graphics, 21(4): 25-34.
- Strogatz, S. H. (2001)
Exploring complex networks.
Nature, 410(6825): 268-276.
- Travers, J. and Milgram, S. (1969)
An experimental study of the small world problem.
Sociometry, 32(4): 425-443.
- Watts, D. J. (1999)
Kevin Bacon, the small-world, and why it all matters.
Santa Fe Institute Bulletin, 14(2): center section.
- Watts, D. J., Dodds, P. S. and Newman, M. E. J. (2002)
Identity and search in social networks.
Science, 296(5571): 1302-1305.
- Watts, D. J. and Strogatz, S. H. (1998)
Collective dynamics of "small-world" networks.
Nature, 393(6684): 440-442.
- Williams, R. J. and Martinez, N. D. (2000)
Simple rules yield complex food webs.
Nature, 404(6774): 180-183.
- Wolfram, S. (2002)
A New Kind of Science. Wolfram Media.
- Young, D. (1984)
A local activator-inhibitor model of vertebrate skin patterns.
Mathematical Biosciences, 72: 51-58.
|