Complex Systems Reading Group
During the fall term, we will meet at 7pm on Wednesdays at the Old Town tavern on
the corner of E. Liberty and S. Ashley streets in Ann Arbor. Our first,
organizational meeting will be Wednesday, September 12.
PS: To be added to the email list for reading group announcements,
send an email to csrg-announce-subscribe@yahoogroups.com or visit
http://groups.yahoo.com/group/csrg-announce on the web.
This email list is moderated and low-volume.
Meeting on Wed., September 19, 7pm at the Old Town
The UM Complex Systems Reading Group invites you to join us this semester
on Wednesdays from 7-9pm at the Old Town tavern on the corner of E.
Liberty and S. Ashley streets in Ann Arbor. There we will discuss papers
related to complex systems, enjoy good food and drink, engage in
stimulating conversation, relax after a hard day of thinking deep
thoughts, and plot the coming complexity revolution. All are welcome,
including those under 21.
This term our theme will be "applications of complex systems". Our first
meeting will be Wednesday, September 19, at 7pm at the Old Town, where we
will discuss:
H.V.D. Parunak, S.A. Brueckner, J. Sauter, and J. Posdamer. "Mechanisms
and Military Applications for Synthetic Pheromones." In Proceedings of
Workshop on Autonomy Oriented Computation at the Fifth International
Conference on Autonomous Agents, Montreal, Canada, 29 May 2001.
http://www.anteaters.net/~sbrueckner/publications/2001/aoc2001.pdf
To subscribe to the moderated, low-volume email list for reading group
announcements, send email to csrg-announce-subscribe@yahoogroups.com or
visit http://groups.yahoo.com/group/csrg-announce on the web.
Meeting on Wednesday, October 3 at 7pm at the Old Town (Liberty and Ashley)
At the next complex systems reading group meeting on Wednesday, October 3
at 7pm at the Old Town (Liberty and Ashley), we will discuss a paper on
evolving cellular automata to predict diseases such as heart disease based
on genetic data:
Moore, Jason H., and Lance W. Hahn. (in press). A cellular automata
approach to detecting interactions among single-nucleotide polymorphisms
in complex multifactorial diseases. Pacific Syposium on Biocomputing.
http://www-personal.umich.edu/~streak/papers/others/moore.pdf
http://www-personal.umich.edu/~streak/papers/others/moore.ps
http://www-personal.umich.edu/~streak/papers/others/moore.doc
Abstract:
The identification and characterization of susceptibility genes for common
complex multifactorial human diseases remains a statistical and
computational challenge. Parametric statistical methods such as logistic
regression are limited in their ability to identify genes whose effects
are dependent solely or partially on interactions with other genes and
environmental exposures. We introduce cellular automata (CA) as a novel
computational approach for identifying combinations of single-nucleotide
polymorphisms (SNPs) associated with clinical endpoints. This alternative
approach is nonparametric (i.e. no hypothesis about the value of a
statistical parameter is made), is model-free (i.e. assumes no particular
inheritance model), and is directly applicable to case-control and
discordant sib-pair study designs. We demonstrate using simulated data
that the approach has good power for identifying high-order nonlinear
interactions (i.e. epistasis) among four SNPs in the absence of
independent main effects.
Meeting on Wednesday, October 10 at 7pm at the Old Town (Liberty and Ashley)
At our next meeting, on Wed., Oct. 10 at 7pm at the Old Town (Liberty and
Ashley) we'll discuss:
Hofmeyr, Steven A., and Stephanie Forrest. (2000). Architecture for an
artificial immune system. Evolutionary Computation 8(4):443-473.
http://www-personal.umich.edu/~streak/papers/others/hofmeyr_forrest.pdf
ftp://ftp.cs.unm.edu/pub/forrest/hofmeyr_forrest.ps
For those on the UM network, the PDF is also available at:
http://cherubino.catchword.com/vl=4695904/cl=36/nw=1/rpsv/catchword/mitpress/10636560/v8n4/s5/p443
Other papers and information about this project are available at:
http://www.cs.unm.edu/~immsec
Abstract:
An artificial immune system (ARTIS) is described which incorporates many
properties of natural immune systems, including diversity, distributed
computation, error tolerance, dynamic learning and adaptation and
self-monitoring. ARTIS is a general frame- work for a distributed adaptive
system and could, in principle, be applied to many domains. In this paper,
ARTIS is applied to computer security, in the form of a network intrusion
detection system called LISYS. LISYS is described and shown to be
effective at detecting intrusions, while maintaining low false positive
rates. Finally, similarities and differences between ARTIS and Holland's
classifier systems are discussed.
As always, I need suggestions of application papers for future readings!
Also, there's a possibility that we might devote next term's reading group
to reading and discussing Doug Hofstadter's book "G�del, Escher, Bach". If
you have comments for or against this, send them to me or to
csrg-discuss@yahoogroups.com.
-Ted
Meeting on Wednesday, October 17 at 7pm at the Old Town (Liberty and Ashley)
At our next meeting, Wednesday, Oct. 17 at 7pm at the Old Town (corner of
Liberty and Ashley), the complex systems reading group will discuss:
Small, Cathy. (1999). Finding an invisible history: A computer simulation
experiment (in virtual Polynesia). Journal of Artificial Societies and
Social Simulation 2(3). <http://www.soc.surrey.ac.uk/JASSS/2/3/6.html>
Abstract:
A modeled Polynesian society is used to explain why, in Polynesia,
growing stratification did not result in a devaluation of women's status,
as most theorists would predict. The computer model used to explore this
problem--called TongaSim--is a C++ program that attempts to emulate the
basic social dynamics of Tonga, a Western Polynesian society. The program
is capable of simulating the operation of a chiefdom with up to 100+
chiefly lines whose descendants marry and have children, create and
maintain kinship relationships, exact and pay tribute, produce and
redistribute agricultural wealth, expand in territory and go to war, and
attempt to gain personal and group status.
TongaSim was used to simulate the effect of warfare (a prime mover of
stratification) on women's status, specifically the custom of "fahu" that
asserts the spiritual superiority of sisters and sister's lines over
brothers and their lines. Because of intermarriage patterns, this custom
also serves to make higher status chiefly lines superior in kinship to
lower status chiefly lines and, thus, supports traditional political
power. Two simulations were conducted with the model--one with warfare OFF
(inactivated) and one with warfare ON, allowing challenging lower chiefs
to go to war and seize land if they were able to do so. The effect of
warfare on the fahu custom and its implications in the virtual system were
recorded and examined. The simulation showed that, despite the initial
conflict between the interests of rising military chiefs and the fahu
custom, the custom was appropriated by these rising chiefs, turning the
fahu's political effects "on its head." Ultimately in the simulation, the
fahu custom provided a vehicle for military chiefs to gain status and
power. This, it is argued, is consistent with the lack of any historical
evidence that the fahu was challenged and toppled during periods of
growing warfare and stratification.
Meeting on Wednesday, October 24 at 7pm at the Old Town (Liberty and Ashley)
At our next meeting, Wednesday, Oct. 24 at 7pm at the Old Town (corner of
Liberty and Ashley), the complex systems reading group will discuss:
Kohler, Timothy A., and Eric Carr. (1997). Swarm-based modelling of
prehistoric settlement systems in southwestern North America. In Ian
Johnson & MacLaren North (eds), Archaeological Applications of GIS:
Proceedings of Colloquium II, UISPP XIIIth Congress, Forli, Italy,
September 1996. Sydney University Archaeological Methods Series 5
(CD-ROM).
http://www.archaeology.usyd.edu.au/resources/documents/kohler/
Abstract [actually from another of their papers]:
Archaeologists have long been interested in why ancient peoples located
their settlements where they did and why these settlements were abandoned.
These questions have always been approached by comparing known site
distributions with resource distributions of various types, possibly (but
not often) taking into account how resource distributions might have been
different in prehistory. It has never been possible, with these
techniques, to also model the effect of humans on the landscapes they
occupy. Recently, these inductive settlement pattern studies have been
greatly aided by GIS and a growing battery of statistical techniques. Here
we report the first stages of a long-term project to begin understanding
settlement processes by departing from household-level decision-making
rather than from the archaeological record. We simulate the placement of
residences and of population growth and decline, as they respond to
changing maize production opportunities and local human impact on the
environment, in southwestern Colorado between A.D. 900 and 1300. The
effort combines GIS data planes and agent-based modeling in a way that
seems promising for many observational sciences.
NOTE: I'm currently planning on holding a meeting on Halloween, as usual.
If you object, please let me know now.
-Ted
Meeting on Wednesday, November 7 at 7pm at the Old Town (Liberty and Ashley)
At our next meeting, Wednesday, November 7 at 7pm at the Old Town (corner of
Liberty and Ashley), the complex systems reading group will discuss:
Wootton, J. Timothy. (2001). Local interactions predict large-scale
pattern in empirically derived cellular automata. Nature 413: 841-844.
PDF:
http://www-personal.umich.edu/~streak/papers/others/wootton.pdf
UM network:
http://www.nature.com/cgi-taf/DynaPage.taf?file=/nature/journal/v413/n6858/abs/413841a0_fs.html
Abstract:
An important unanswered question in ecology is whether processes such as
species interactions that occur at a local scale can generate large-scale
patterns seen in nature. Because of the complexity of natural ecosystems,
developing an adequate theoretical framework to scale up local processes
has been challenging. Models of complex systems can produce a wide array
of outcomes; therefore, model parameter values must be constrained by
empirical information to usefully narrow the range of predicted behaviour.
Under some conditions, spatially explicit models of locally interacting
objects (for example, cells, sand grains, car drivers, or organisms),
variously termed cellular automata or interacting particle models, can
self-organize to develop complex spatial and temporal patterning at larger
scales in the absence of any externally imposed pattern. When these models
are based on transition probabilities of moving between ecological states
at a local level, relatively complex versions of these models can be
linked readily to empirical information on ecosystem dynamics. Here, I
show that an empirically derived cellular automaton model of a rocky
intertidal mussel bed based on local interactions correctly predicts
large-scale spatial patterns observed in nature.
Meeting on Monday, December 3 at 7pm at the Old Town (Liberty and Ashley)
At our next meeting, Monday, December 3 at 7pm at the Old Town (Liberty
and Ashley), under the Rubenesque painting in back, we will read:
Riolo, Rick L., Michael D. Cohen, and Robert Axelrod. (2001). Evolution of
cooperation without reciprocity. Nature 414: 441-443.
http://www.nature.com/cgi-taf/DynaPage.taf?file=/nature/journal/v414/n6862/full/414441a0_fs.html
http://www-personal.umich.edu/~streak/papers/others/car.pdf
and:
Sigmund, Karl, and Martin A. Nowak. (2001). Evolution: Tides of tolerance.
Nature 414: 403-405.
http://www.nature.com/cgi-taf/DynaPage.taf?file=/nature/journal/v414/n6862/full/414403a0_fs.html
http://www-personal.umich.edu/~streak/papers/others/sigmund-nowak.pdf
