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INFORMATION
Please send
inquiries regarding workshops by e-mail to
the workshop chair Jano van Hemert 
Proceedings of the workshops will be published on CD-ROM, and distributed at
the conference.
Call
for workshop proposals, which was closed on 28 October, 2006.
OVERVIEW
 Medical
Applications of Genetic and Evolutionary
Computation Workshop (MedGEC)-
Stephen
L. Smith  & Stefano
Cagnoni 
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Biological applications of Genetic and Evolutionary Computation
(BioGEC)
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Jason Moore  & Marylyn Ritchie 
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- User-centric Evolutionary Computation Workshop
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Ian Parmee
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- Optimization by Building and Using Probabilistic Models (OBUPM)
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Peter
Bosman  , Jörn Grahl  , Kumara Sastry & Martin Pelikan 
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- Military and Security Applications of Evolutionary Computation
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Laurence
Merkle  , Misty Blowers  & Stephen C. Upton 
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Undergraduate Student Workshop
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Laurence
Merkle , Clare Bates Congdon  & Frank
Moore 
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Learning Classifier Systems (LCS)
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Tim Kovacs  , Xavier Llorà  & Keiki Takadama 
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Adaptive Representations
-
Marc
Toussaint  & Edwin de Jong 
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Complexity through Development and Self-Organizing Representations
(CODESOAR)
(previously known as
SEEDS)
-
Julian
Miller  ,
Ivan Garibay  , Sanjeev
Kumar  , Ozlem Garibay  & Kivanc
Oner 
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ABSTRACTS
- Medical
Applications of Genetic and Evolutionary
Computation Workshop (MedGEC)
- Stephen L. Smith & Stefano Cagnoni
- Duration: Half Day
[ further details ]
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- The Workshop will focus on the application
of genetic and evolutionary computation (GEC)
to problems in medicine and healthcare, and.provide
a forum in which researchers can discuss and
exchange ideas, support and advise each other
in theory and practice.
Subjects will include (but are not limited to) applications of GEC to: Medical
imaging; Medical signal processing; Clinical diagnosis and therapy; Data
mining medical data and records; Clinical expert systems; Modeling, and simulation
of medical processes.
Accepted papers will be considered for inclusion in a special issue of the
journal "Genetic Programming and Evolvable Machines".
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Biological
applications of Genetic and Evolutionary Computation
(BioGEC)
-
Jason Moore & Marylyn
Ritchie
- Duration: Full Day
[ further details ]
-
- The fifth annual workshop on
Biological applications of Genetic and Evolutionary
Computation (BioGEC) is intended to explore
and critically evaluate the application of
GEC to a wide range of biological problems.
Specifically, the goal is to bring biologists
and computer scientists together to foster
an exchange of ideas that will yield emergent
properties that will move the field forward
in unpredictable ways. We propose below a new
format for the 2006 BioGEC workshop that will
explicitly bring computer scientists together
with biologists to foster interaction.
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-
User-centric Evolutionary Computation Workshop
Ian Parmee
Duration: Half Day
[ further details ]
Interactive evolutionary computing, in the main, relates to partial or
complete human evaluation of the fitness of solutions generated from evolutionary
search. This has been introduced where quantitative evaluation is difficult
if not impossible to achieve. Examples of application include graphic arts
and animation; food engineering and hazard icon design. Such applications
rely upon a human-centred, subjective evaluation of the fitness of a particular
design, image, taste etc as opposed to an evaluation developed from some
analytic model.
Partial human interaction that complements quantitative machine-based solution
evaluation is also in evidence. For instance, the user addition of new
constraints in order to generate solutions that are fully satisfactory
within evolutionary scheduling systems or the introduction of designer-generated
solutions into selected evolving generations.
Solutions can also provide information to the user which supports a better
understanding of the problem domain whilst helping to identify best direction
for future investigation especially when operating within poorly defined
problem spaces. This supports development of the problem representation
in an iterative, interactive evolutionary design and decision-making environment.
Such human-centric approaches generate and succinctly present information
appertaining to complex relationships between the variables, objectives
and constraints that define a decision space.
In an attempt to categorise these various forms of IEC it is possible to
view complete human evaluation as explicit whereas partial evaluation and
interaction are less explicit, more subtle forms of human involvement.
Completely implicit interaction occurs where users are unaware of their
role in the evolution of a system e.g. the on-line evolution of web-based
tutorials based upon the manner users are navigating the system and their
associated degree of success. A simple implicit/explicit spectrum of interactive
evolutionary approaches can thus be developed.
- Optimization by Building and Using Probabilistic Models (OBUPM)
-
Peter Bosman,
Jörn Grahl, Kumara Sastry & Martin
Pelikan
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Duration:
Half Day
-
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- Genetic- and evolutionary
algorithms (GEAs) evolve a population of
candidate solutions to a given optimization
problem using two basic operators: (1) selection
and (2) variation. Selection introduces a
pressure toward high-quality solutions, whereas
variation ensures exploration of the space
of all potential solutions. Two variation
operators are common in current genetic{
and evolutionary computation (GEC): (1) crossover,
and (2) mutation. Crossover creates new candidate
solutions by combining bits and pieces of
promising solutions, whereas mutation introduces
slight perturbations to promising solutions
to explore their immediate neighborhood.
However, fixed, problem-independent variation
operators often fail to effectively exploit
important features of high-quality selected
solutions. One way to make variation operators
more powerful and flexible is to replace
traditional variation of GEAs by the following
two steps: 1. Build a probabilistic model
of the selected promising solutions, and
2. sample the built model to generate a new
population of candidate solutions. Algorithms
based on this principle are commonly called
estimation-of-distribution algorithms (EDAs)
but are also known as probabilistic model-building
genetic algorithms (PMBGAs) and as iterated
density{estimation evolutionary algorithms
(IDEAs). The general purpose of this workshop
is to present and discuss
- recent advances in
EDAs,
- new theoretical and
empirical results,
- applications of EDAs,
and
- promising directions
for future EDA research.
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Military
and Security Applications of Evolutionary Computation
- Laurence Merkle & Misty Blowers
Duration:
Full Day
[ further
details ]
Almost since its inception, evolutionary computation
has been applied
to the solution of military problems. Since September
11, 2001, there
has been increased interest within the military
and security
communities in novel techniques for solving challenging
problems within
their domains. The genesis of this interest lies
in the fact that
repeated attempts of using traditional techniques
have left many
important problems unsolved, and in some cases,
not addressed.
Additionally, new problems have emerged within
the broad areas of the
global war on terrorism, homeland security, and
force protection that
are difficult to tackle with conventional methods,
since social,
cultural and human behavioral factors tend to
be at the heart of these
new types of problems. The purpose of the workshop
is to continue our
discussion of current and ongoing efforts in
using genetic and
evolutionary computation techniques in attacking
military and security
problems. These include, but are not limited
to the following:
•
Genetic and evolutionary techniques in the design
of military systems
and sub-systems;
•
Genetic and evolutionary techniques for logistics
and scheduling of
military operations;
•
Genetic and evolutionary algorithms (GEAs) in
strategic planning and
tactical decision making;
•
Multiobjective GEAs for examining tradeoffs in
military, security,
and counter-terrorism procedures;
•
Automated discovery of tactics and procedures
for site security,
force protection, and consequence management;
•
Genetics-based knowledge discovery and data mining
of large databases
used to recognize patterns of individual behavior;
and
•
Co-evolutionary techniques for simultaneous red-blue
team
strategic-tactical simulation and gaming.
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Undergraduate Student Workshop
Laurence Merkle , Clare Bates Congdon & Frank
Moore
Duration: Half Day
[ further details ]
Goals of the workshop include:
-
providing
a forum allowing undergraduate students
to put a "capstone" on their undergraduate
research activities, through presentation
of their work at an international
conference;
-
encouraging
teaching faculty to think about undergraduate
research opportunities for their
students in the evolutionary computation
field;
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preparing
standout undergraduate students for
graduate studies in the evolutionary
computation field;
-
encouraging
more focus on education amongst GECCO
participants;
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recruiting
opportunities for faculty at advanced
degree granting institutions; and
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sharing
and networking amongst teaching faculty
with students participating in undergraduate
research.
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Learning Classifier Systems (LCS)
Tim Kovacs, Xavier Llorà & Keiki Takadama
Duration: Full Day
[ further details ]
Since Learning Classifier Systems (LCSs) were introduced by Holland as
a way of applying evolutionary computation to machine learning problems,
the LCS paradigm has broadened greatly into a framework encompassing
many representations, rule discovery mechanisms, and credit assignment
schemes. Current LCS applications range from data mining to automated
innovation to on-line control. Classifier systems are a very active area
of research, with newer approaches, in particular Wilson?s accuracy-based
XCS, receiving a great deal of attention. LCS are also benefiting from
advances in the field of reinforcement learning, and there is a trend
toward developing connections between the two areas.
We invite submissions which discuss recent developments in all areas
of research on, and applications of, Learning Classifier Systems.
IWLCS is the only event to bring together most of the core researchers
in classifier systems. A free introductory tutorial on LCS will be presented
at GECCO 2006.
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Adaptive Representations
Marc Toussaint & Edwin de Jong
Duration: Half Day
[ further
details ]
Nature has developed an ingenious language to describe organisms: the
genetic system. From theory we know that the choice of representation
has a crucial influence on the search distribution and the chances to
find solutions in a search process. In this view, how can we learn a
suitable representation from previous evaluations of samples that will
facilitate the search for better solutions? And how can continuous self-adaptation
of the representation in evolutionary processes be performed and understood?
In this workshop we would like to gather work from different approaches
to these questions and initiate a discussion, particularly between people
from different theoretical, experimental, or biological backgrounds,
aiming at a common framework and language to address such questions.
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(previously known as
SEEDS)
Julian Miller , Ivan Garibay , Sanjeev
Kumar , Ozlem Garibay & Kivanc Oner
Duration: Full Day
[ further details ]
This workshop follows on from the successful workshops on
self-organization in representations in evolutionary algorithms, and
scalable, evolvable, emergent developmental systems at previous GECCO
conferences. This year's workshop is a unified workshop covering both
closely related areas. It promises to be an exciting, thought
provoking,
and successful workshop.
This workshop will focus on domain-independent methods for representing
complex solutions with self-organizable building blocks, and on
developmental principles for specifying the construction of complex
systems. The workshop welcomes multidisciplinary work, including
submissions from biologists on relevant biology that may help shed
more
light on developmental, self-organizing principles for evolutionary
computation.
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