Madison
Chaos and Complex Systems Seminar
Fall 1996 Seminars
Dates, speakers, titles and abstracts will be listed as they become
available.
Meetings will be noon Tuesdays in 4274 Chamberlin Hall unless
otherwise
noted.
Short List
- 3 September. Steering Committee
Meeting.
- 10 September. Bill Lytton: ``The
Thalamic
Oscillator:
Complex Cell or Simple Network?''
- 17 September. Jean-Paul Chavas:
``Dynamics
and Economic
Rationality.''
- 24 September. Scott Kelso: ``How
Things
Work
Together:
The Problem of Coordination.''
- 1 October. W. A. Brock: ``Evolutionary
Theories
of
the Stock Market.''
- 8 October. Chris Demarco. ``Predicting
Dynamic
Behavior
in Large Scale Electric Power Networks: the Anatomy of
Blackout.''
- 15 October. Rick Jenison: ``Dynamic
Bayesian
Estimation
of Time-to-Arrival from Acoustic Information.''
- 22 October. Bob Savit: ``Time
Dependence
in
Complex
Systems.''
- 29 October. David Albers: ``Dynamical
Behavior
of
Artificial Neural Networks with Random Weights.''
- 5 November. Richard Belew: ``Competitive
Co-evolution.''
- Related Lecture: 11 November.
John
Lisman:
``The Role of Brain Oscillations in Long Term and Short Term
Memory.''
- 12 November. Robert Meyer: ``A Genetic
Algorithm for
Optimal Domain Decomposition.''
- Related Lecture: 15 November.
Stuart
Zola:
``Brain Circuitry of Memory and Memory Loss: Findings from
Humans and
Nonhuman
Primates.''
- Realted Lecture: 15 November.
Josh
Chover:
``Sequential Recall.''
- 19 November. Paul Terry: ``Impeding
Turbulent
Transport:
From Fusion Reactors to the Ozone Hole.''
- 26 November. George Hrabovsky:
``Transient
Chaos in
Accretion Disks.''
- Related Lecture: 26 November.
Subbarao
Palacharla:
``Quantifying the Complexity of Superscalar Processors.''
- 3 December. Virginia Young: ``Creating
an
Expert System
from Linguistic Rules--A Fuzzy Logic Approach.''
- 10 December. Christopher Kribs: ``A
Two-Sex
STD Model
with Recruitment and Activity Levels.''
3 September. Steering Committee Meeting
Speaker nomination and recruitment. Funding. Possible themes for
series
of talks.
10 September. Bill Lytton, UW Neurology.
``The
Thalamic
Oscillator: Complex Cell or Simple Network?''
Abstract: Neurons are complex dynamical systems with multiple
internal
interactions that are presumably relevant to their information
processing
role. We have used computer modeling to investigate the neurons of
the
thalamus, a central nuclear complex that serves both as a
way-station
for
sensory input and as a central oscillator during sleep. Three main
cell
types make up the thalamic network: thalamocortical cells (TC),
reticularis
cells (RE) and thalamic interneuron (INT). Depending on membrane
voltage,
each neuron type can by itself produce oscillatory behavior.
Connected
together, they influence each other's phase and frequency to produce
the
oscillatory patterns of the thalamus as a whole.
17 September. Jean-Paul Chavas, UW
Agricultural Economics.
``Dynamics and Economic Rationality.''
Abstract: Economic rationality and efficient resource
allocation
are typically defined in the context of optimizing behavior. This
raises
the question: Under what conditions does optimizing behavior
generate
simple
dynamics (e.g., convergence to a steady-state equilibrium)? And
under
what
conditions does it generate complicated dynamics (e.g., limit cycles
or
chaos)? Implications are discussed concerning the formulation and
solution
of dynamic optimization problems, the explanation of business
cycles,
and
the characterization of economic rationality.
24 September. J. A. Scott Kelso, Center for
Complex
Systems, Florida Atlantic University. ``How Things Work Together:
The
Problem
of Coordination.''
Abstract: Coordination is a fundamental feature of living
things,
implying some kind of functional order in which the ``whole is
greater
than and different from the parts''. Historically, ideas from
Gestalt
psychology,
Bernstein's synergy concept, Weiss's notion of self-differentiation,
von
Holst's principle of central coordination are all attempts to come
to
grips
with the coordination problem. Only recently have these intuitions
been
provided a firm theoretical and empirical foundation. Building upon
the
concepts and methods of pattern formation in nonequilibrium systems,
coordination
dynamics aims to find the basic rules for how coordination states
form
and change. The first part of this talk reviews some research in
which
it has been possible to identify relevant coordination variables and
their
dynamics for several different kinds of system (e.g. parts of the
organism,
the organism responding to signals from its environment, organisms
interacting
with each other). Importantly, predictions of the theory have been
subject
to experimental tests, a process that has led to new theoretical
developments.
The second part of the talk will describe how the strategy of
coordination
dynamics, in which instability plays a key conceptual and
methodological
role, has been extended to the study of how parts of the brain are
coordinated
with each other and with behavior itself. Work is underway that
attempts
to derive earlier phenomenological models of brain and behavioral
function
from a deeper theory grounded in current knowledge about cortical
anatomy
and neurophysiology. If there is time, I will talk about what all
this
might mean for the coordination of mind, brain and behavior.
1 October. W. A. Brock, UW Economics.
``Evolutionary
Theories of the Stock Market.''
Abstract: This talk gives a tour of recent efforts to modify
the
standard rational expectations literature to include expensive
acquisition
of rational expectations. For financial models fitness of an
expectation
or belief system is past trading profits net cost of acquisition.
The
distribution
of fitnesses changes over time. There are periods where markets run
``tight''
and periods where they run ``loose.'' This is so because if everyone
buys
expensive but more accurate expectations then the profit is competed
away
to the extent that the acquisition cost is not covered and vice
versa.
This tension can create complicated dynamics. A discussion will be
given
of problems that deterministic dynamical systems models face in
generating
patterns that look like real stock market data.
8 October. Chris Demarco, UW Electrical and
Computer
Engineering. ``Predicting Dynamic Behavior in Large Scale Electric
Power
Networks: the Anatomy of Blackout.''
Abstract: The North American electric power network is
composed
of hundreds of thousands of electromechanical devices, coupled by a
transmission
grid of continental scale. The composite behavior of this huge
interconnected
system can be highly complex. This behavior is further complicated
by
the
unavoidable occurrance of indivdual equipment faliures, and the
presence
of an overlaid protection system that can instantaneously disconnect
additional
pieces of equipment when local overloads are detected. This talk
will
give
an overview of typical disturbance scenarios in such systems, taking
the
recent western US blackouts of July and August '96 as motivating
examples.
We will continue by providing an overview of the basic structure of
the
underlying electromechanical dynamics, and describe how these
interact
with protective devices in a manner that may be modeled as a
``discrete
event'' system. To efficiently operate a modern power grid, it is
clearly
desirable to be able to predict the dynamic response of the system
to
anticipated
disturbances. This talk will briefly survey the current state of the
art
in simulation tools for this purpose, and will highlight current
research
efforts at UW-Madison that seek to augment these with analytic tools
for
assessing qualitative behavior.
15 October. Rick Jenison, UW Psychology.
``Dynamics
Bayesian Estimation of Time-to-Arrival from Acoustic
Information.''
Abstract: Much of the interest regarding an active observer
has
centered on precise timing of interactions with objects in the
environment
in relation to observers, for example, a baseball player catching a
fly
ball. An observer seeks new information by exploring the
environment.
This
means moving around, tracking objects in space, and avoiding
collisions.
These examples certainly seem natural for the visual sense, but what
about
audition? Although the physical nature of optics and acoustics are
different,
both kinds of information can be shown to sufficiently specify the
geometry
or kinematics of moving objects relative to an observer.
Theoretical work on optic information for time-to-arrival has
focused
on a variable commonly referred to as ``tau'' that specifies the
time-to-direct-contact
from the optical dilation of an approaching object at any instant
in
time.
An analysis similar to that for visual tau has been applied to
acoustic
structure to derive an analogous acoustic tau based on detected
changes
in sound intensity. Change in sound intensity is but one source of
information
for specifying motion parameters of a sound-emitting object in
space.
Changes
in binaural and spectral structure in the forms of dynamic
interaural-time-delay,
interaural-intensity-differences, and Doppler shifts are also
available.
In this talk, a dynamical system for integrating acoustic
information
that
specifies time-to-arrival (and parameters of object motion in
general)
is presented. This model is based on Bayesian data-fusion
techniques
that
have been developed in the field of passive sonar. Although these
measurement
equations are nonlinear, they can be linearized sufficiently to
utilize
standard Kalman filtering techniques as recursive estimators of
motion-state
variables. Theoretical lower bounds can be established using the
Cramer-Rao
lower bound on the recursive estimators, which gives the minimum
variance
that an unbiased estimator can achieve from a series of noisy
measurements.
22 October. Bob Savit, Department of
Physics,
University
of Michigan. ``Time Dependence in Complex Systems.''
Abstract: Time series generated by complex, nonlinear systems
are
notoriously difficult to analyze. One important problem that must be
addressed
early on, is whether the underlying dynamics driving the process is
time
independent. This question is related to, but not the same as, the
question
of stationarity. In this talk I will describe a new method for
analyzing
time series from complex systems that is designed to uncover time
dependence
in the underlying dynamics. In addition to addressing the question
of
whether
the underlying dynamics is time dependent or not, the approach
provides
insight into the nature of the time dependence, if it exists. I will
discuss
applications of the method to the analysis of intracranial EEG
recordings
from patients with temporal lobe epilepsy, to a problem in
mechanical
vibration
analysis, as well as to some examples of simulated data.
29 October. David Albers, UW Physics.
``Dynamical Behavior
of Artificial Neural Networks with Random Weights.''
Abstract: In this talk I will describe a Monte Carlo study of
large
untrained, feedforward, neural networks with randomly chosen weights
and
feedback. The analysis consists of looking at the percent of the
systems
that exhibit chaos, the distribution of largest Lyapunov exponents,
and
the distribution of correlation dimensions. As the systems become
more
complex (increasing inputs and neurons), the probability of chaos
approaches
unity. The correlation dimension is typically much smaller than the
system
dimension.
5 November. Richard K. Belew, CSE Dept. ---
UC
San Diego
and CS Dept. --- UW (Visiting). ``Competitive Co-evolution.''
Abstract: Many of the most important design problems are
difficult
not only because there are a vast number of solutions to consider,
but
also because the number of TESTS for potential solutions is vast as
well.
We analyze the ``competition dynamic'' between solutions and tests
as
it
arises in evolutionary computations: Two distinct populations of
``hosts''
and ``parasites'' are maintained, with increasing reproductive
success
of individuals in one population being at the expense of those in
the
other.
The resulting search is related to the theory of PAC learning, and
several
heuristics are demonstrated to significantly improve the
evolutionary
algorithm's
search behavior. Game-playing applications are shown to be a very
natural
domain for these methods, and some prelimary results applied to the
board
game of Go are presented.
This work is based on an upcoming dissertation by Chris Rosin,
CSE/UCSD.
11 November. Related Lecture. John
Lisman, Volen
Center for Complex Systems, Brandeis University. ``The Role of
Brain
Oscillations
in Long term and Short Term Memory.''
Unusual time and place: Monday, 3:30 pm, room 341 Bardeen.
Sponsored by the Center for Neuroscience (Ken Mack, 263-9800, or
Peter
Lipton, 262-1709, for more information or contact with Dr.
Lisman).
12 November. Robert Meyer, UW Computer
Sciences.
``A
Genetic Algorithm for Optimal Domain Decomposition.''
Abstract: The problem of ``optimally'' partitioning a given
domain
into a specified number of pieces arises in a variety of computer
science
applications, from database to image analysis to partial
differential
equations.
The general goal in all of these applications is to obtain pieces
that
are of nearly equal size (for load balancing in parallel computing
environments)
and, in addition, have small perimeter (in the two-dimensional case)
or
small surface area (in the three-dimensional case), thereby reducing
communication
costs. This type of problem fits well into the genetic algorithm
paradigm
since it can be formulated in terms of trying to determine and
combine
good ``building blocks'' (well-shaped pieces of the domain) to
obtain a
good overall solution. We present a genetic algorithm that
outperforms
existing approaches to domain decomposition because it makes
effective
use of this high-level building block information.
15 November. Related Lecture. Stuart
Zola: ``Brain
Circuitry of Memory and Memory Loss: Findings from Humans and
Nonhuman
Primates.''
Unusual time and place: Friday, 12 noon in room 113
Psychology.
A University Lecture sponsored by the Psychology Department and
co-sponsored
by the Primate Center and the Department of Psychiatry. ``Dr. Zola
is
an
internationally renowned researcher on neural mechanisms of memory
formation
and memory loss, whose work spans both animal models and humans,
using
a variety of manipulative and imaging methodologies.'' Contact for
information:
Craig Berridge, Psychology Dept.
15 November. Related Lecture. Josh
Chover,
UW Math. ``Sequential Recall.''
Abstract: I'll discuss a simple two-layer neural network
model
which
has sparse forward, lateral, and feedback connections. Simulations
demonstrate
an ability for quick recall of a sequence of overlapping inputs,
given
an initial prompt--inputs learned in an unsupervised way. The
dynamics
are not based on iteration to a limit. The model suggests roles for
biological
counterparts, such as modifiable and non-modifiable channels.
19 November. Paul Terry, UW Physics.
``Impeding
Turbulent
Transport: From Fusion Reactors to the Ozone Hole.''
Abstract: There is no universal theory of turbulence, given
the
lack of universality in the dynamical behavior of different systems.
However
a recently discovered phenomenon runs counter to this trend and
appears
to operate in essentially the same fashion in systems ranging from
fusion
plasmas to the earth's middle atmosphere. This phenomenon,
suppression
of turbulence and turbulent mixing by sheared flow, has been
credited
with
removing turbulent transport in fusion devices. It may also apply to
transport
barriers in the stratosphere, confinement of salinity and heat in
long-lived
vortical ocean currents, and intermittency in 2D Navier-Stokes
turbulence.
This phenomenon will be described heuristically and its application
to
some of the above problems will be discussed.
26 November. George E. Hrabovsky, UW
Physics.
``Transient
Chaos in Accretion Disks.''
Abstract: This talk will discuss transient chaos in accretion
disks
(disks of matter which spiral in to a source of intense gravitation
such
as black holes and neutron stars). A review of topics involving
circle
maps, transient chaos, diffusion, and accretion will be a part of
the
talk.
26 November. Related Lecture.
Subbarao
Palacharla,
UW Computer Sciences. ``Quantifying the Complexity of Superscalar
Processors.''
Unusual Time and Place: 4pm, room 1325 Computer Sciences
building.
Abstract: This talk consists of two parts. The first part
describes
our attempt at quantifying the complexity of superscalar
processors.
First,
a generic superscalar pipeline is defined. Then, the specific
areas of
register renaming, window wakeup and selection logic, and operand
bypassing
are analyzed. Performance (delay) results and trends are expressed
in
terms
of issue width and window size. Our analysis indicates that window
logic
and operand bypass logic are likely to be the most critical in the
future.
The second part of the talk describes a microarchitecture that
simplifies
window logic. This dependence-based microarchitecture puts
dependent
instructions
into multiple queues, and issues them from the queues in strict
FIFO
order.
Simulation shows little slowdown as compared with a completely
flexible
issue window, when performance is measured in clock cycles.
Furthermore,
because only instructions at FIFO heads need to be awakened and
selected,
issue logic is simplified and the clock cycle is faster --
consequently
overall performance is improved. Also, the proposed
microarchitecture,
by grouping dependent instructions together, helps minimize the
performance
degradation due to slow bypasses in future wide-issue machines.
3 December. Virginia Young, UW School of
Business. ``Creating
an Expert System from Linguistic Rules--A Fuzzy Logic Approach.''
Abstract: Fuzzy logic was developed in the 1970's to provide
a
way
to account for the vagueness inherent in linguistic rules. I will
give
a brief background into fuzzy sets themselves and will describe how
one
can use fuzzy logic to create an expert system by starting with
linguistic
rules. I will illustrate my method with a simple hypothetical
example
from
insurance pricing.
10 December. Christopher Kribs, UW Math. ``A
Two-Sex
STD Model with Recruitment and Activity Levels.''
Abstract: In this talk I will present a brief overview of
dynamical
systems that have been used to model the spread of a disease within
a
population,
and then discuss a particular model I have developed which
incorporates
division of the population both by gender and by contact rate (here
interpreted
as sexual activity levels), separations which normally have not been
modeled
simultaneously because of the inherent complexity of the model(s).
Analysis
of the model yields results which differ from those of simpler
models:
in particular, the coexistence of two stable equilibria, so that
local
stability does not imply global stability. The physical assumptions
for
the model are based on studies of sexually transmitted diseases with
eventual
recovery (e.g., gonorrhea). My emphasis will be on results and their
implications
rather than their derivations.
Up to the Chaos and Complex Systems Seminar
page.
Last change worth mentioning Mon Nov 25 10:46:05 1996
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