GECCO 2015
Workshops:
Organisers
1. Genetic Improvement 2015
- W. B. Langdon (University College, London, UK)
- David R. White (University of Glasgow, UK)
- Justyna Petke (University College, London, UK)
2. SecDef'2015 - Workshop on genetic and evolutionary computation
in defense, security and risk management
- Frank W. Moore (University of Alaska Anchorage, USA?)
- Nur Zincir-Heywood (Dalhousie University, Canada)
3. Workshop on Evolutionary Computation in Computational
Structural Biology
José Santos (University of A Coru?a, Spain)
- Julia Handl (University of Manchester, UK)
- Amarda Shehu (Georgia Mason University, US)-
4. 6th Workshop on Visualisation Methods in Genetic and
Evolutionary Computation (VizGEC 2015)
- David Walker (University of Exeter, UK)
- Richard Everson (University of Exeter, UK)
- Jonathan Fieldsend (University of Exeter, UK)
5. Evolutionary Rule-based Machine Learning
(former Int.
Workshop on Leaning Classifier Systems)
- Karthik Kuber (Microsoft, Redmond, US?)
- Masaya Nakata (The University of Electro-Communications, Japan)
- Kamran Shafi (University of New South Wales, Australia)
6. 5th Workshop on Evolutionary Computation for
the Automated Design of Algorithms (ECADA)
- John Woodward (University of Stirling, UK)
- Daniel Tauritz (Missouri University of Science and Technology, US)
- Manuel López-Ibá?ez
7. Workshop on Evolutionary Computation Software Systems (EvoSoft)
- Dr. Stefan Wagner (University of Applied Sciences Upper, Austria)
- Dr. Michael Affenzeller (University of Applied Sciences Upper,
8. Black Box Optimization Benchmarking 2015 (BBOB 2015)
- Youhei Akimoto (Shinshu University, Japan)
- Anne Auger (INRIA Saclay, France)
- Dimo Brockhoff
Lille, France)
- Nikolaus Hansen (INRIA Saclay, France)
- Olaf Mersmann (Technische Universitaet Dortmund, Germany)
- Petr Po?ik (Czech Technical University, Prague)
9. GECCO Student workshop
- Tea Tu?ar (Jozef Stefan Institute, Slovenia)
- Boris Naujoks (Cologne University of Applied Sciences, Germany)
10. Evolving Collective Behaviors in Robotics
- Abraham Prieto (University of A Coru?a, Spain)
- Nicolas Bredeche (Universite Pierre et Marie Curie,
- Evert Haasdijk (Vrije University, Amsterdam)
11. Women@GECCO
- Carola Doerr (CNRS & Universite Pierre et Marie Curie (Paris
6), France)
- Anna Esparcia (Universitat Politècnica de València, Spain)
- Gabriela Ochoa (University of Stirling, UK)
- Una-May O'Reilly (MIT, USA)
- Dr. Nur Zincir-Heywood (Dalhousie
University, Canada)
- Emma Hart
(Edinburgh Napier University )
- Christine
Zarges (University of Birmingham, UK)
12. 2nd Workshop on Metaheuristic Design Patterns (MetaDeeP)
- Chris Simons (University of the West of England, UK)
- Jerry Swan (University of Stirling, UK)
- Krzysztof Krawiec (Poznan University of Technology, Poland)
- Daniel Tauritz (Missouri University of Science and Technology, US)
- Jim Smith (University of the West of England, UK)
13. Automatically Configurable Algorithmic Frameworks
14. Semantic Methods in Genetic Programming (SMGP)
- Colin Johnson (University of Kent, UK)
- Krzysztof Krawiec (Poznan University of Technology, Poland)
- Alberto Moraglio (University of Exeter, UK)
- Michael O’Neill (University College Dublin, Ireland)
15. Evolutionary Computation for Big Data and Big Learning
16. Medical Applications of Genetic and Evolutionary Computation
- Stephen L. Smith (University of York, UK)
- Stefano Cagnoni (Universita' degli Studi di Parma, Italy)
- Robert M. Patton, (Oak Ridge National Laboratory, USA)
17. 9th Workshop on Evolutionary Computation and Multi-Agent
Systems and Simulation (ECoMASS)
1.-Genetic Improvement 2015
Lately there has been enormous interest in the use of evolutionary
and genetic search in optimising aspects of software engineering. For example,
since 2002 there has been an SBSE track at GECCO. More recently there is a
dedicated SSBSE conference. Indeed we now see regional conferences and
workshops featuring or even dedicated to Search Based Software Engineering
starting (in China, Brazil and now the USA). Including&to appear,
since 2000, there have been more than 70 papers in this area and interest is
growing. Since 2009 there have been three human competitive awards (Gold,
Silver and Bronze) presented at GECCO and two best papers, including the
International Conference on Software Engineering and GECCO.
Whilst SBSE has traditionally been applied to software engineering
problems there has been great interest in using it, particularly genetic
programming, on software itself.
Genetic Improvement (GI) is the application of evolutionary and
search-based optimisation methods to the improvement of existing software. The
technique was first applied to optimise and find compromises between
non-functional properties of software, such as execution time and power
consumption. This work lead on to automated bug fixing in commercial software.
More recently, it has been shown that GP can use human written software as a
feed stock for GP and is able to evolve mutant software dedicated to solving
particular problems. Another interesting area is grow and graft GP, where
software is incubated outside its target human written code and subsequently
grafted into it via GP.&
Contact: geneticimprovement2015
Biographies
William B. Langdon has been working with
genetic programming since 1993. His current research uses GP to genetically
improve existing software, CUDA, search based software engineering and
Bioinformatics. Indeed GI has been used to significantly improve a widely used
bioinformatics tool, nVidia software running on graphics hardware and a GPU
kernel for NMR medical imaging registration. He co-organised the computational
intelligence on GPUs (CIGPU) series of workshops, the first EvoPAR track in the
European conference on applications of evolutionary computation and last year
was co-chair of the GECCO genetic programming track. His books include A Field
Guide to Genetic Programming, Foundations of Genetic Programming and Advances
in Genetic Programming 3. He also maintains the genetic programming
bibliography.
David R. White
He is a researcher in the School of Computing Science
at the University of Glasgow. He published some of the seminal papers on both
creating new and improving existing software with respect to non-functional improvement,
and his subsequent thesis was nominated for a BCS distinguished thesis award.
He then worked as a SICSA Research Fellow at the University of Glasgow, before
joining the EPSRC AnyScale project. He is on the steering committee of SSBSE
and has won two best paper awards for work in evolutionary search.
Justyna Petke
Dr. Petke has a DPhil in Computer Science from University of
Oxford and is now at the Centre for Research on Evolution, Search and Testing
(CREST) in University College, London. She has published applications of
genetic improvement. One of her recent papers was awarded a HUMIE at this
year's GECCO in Vancouver. Dr. Petke is co-organising the First North American
Search Based Software Engineering Symposium (to be held in February).&
2- SecDef'2015 - Workshop on genetic and evolutionary computation in defense, security and risk management
With the constant appearance of new threats, research in the areas
of defense, security and risk management has acquired an increasing importance
over the past few years. These new challenges often require innovative
solutions and Computational Intelligence techniques can play a significant role
in finding them. The workshop invites completed or ongoing work, with the aim
to encourage communication between active researchers and practitioners to
better understand the current scope of efforts within this domain. The ultimate
goal is to understand, discuss, and help set future directions for
computational intelligence in security and defense problems.
We seek both theoretical developments and applications of Genetic
and Evolutionary Computation and their hybrids to the following (and other
related) topics:
Cyber crime and cyberdefense : anomaly detection systems, attack
prevention and defense, threat forecasting systems, anti spam, antivirus
systems, cyber warfare, cyber fraud &
IT Security: Intrusion detection, behavior monitoring, network
traffic analysis
Corporate security, with special focus on BYOD policies and
usability of security
Risk management: identification, prevention, monitoring and
handling of risks, risk impact and probability estimation systems, contingency
plans, real time risk management
Critical Infrastructure Protection (CIP)
Advanced Persistent Threats (APTs)
Design of military systems and sub-systems.
Logistics and scheduling of military operations.
Strategic planning and tactical decision making.&
Multiobjective techniques for examining tradeoffs in military,
security, and counter-terrorism procedures.
Automated discovery of tactics and procedures for site security,
force protection, and consequence management.
Other computational intelligence techniques for applications in
the areas listed above.
Biographies
Frank Moore
He is Professor and Chair of the Computer Science &
Engineering at the University of Alaska Anchorage. He has taught computer
science and engineering for the past 17 years. He also has over six years of
industry experience developing software for a wide range of military projects.
His recent NASA-funded research (patent pending) used evolutionary computation
to optimize transforms that outperform wavelets for lossy image compression and
reconstruction. He has received over $750,000 in research funding and has
published over 80 technical papers and reports. Dr. Moore is a Senior Member of
ACM and a Member of IEEE.
Nur Zincir-Heywood
Dr. Nur Zincir-Heywood is a Professor of Computer Science at
Dalhousie University, Canada. She received her PhD in 1998 in Computer Science
and Engineering from Ege University, Turkey. Prior to moving to Dalhousie in
2000, Dr. Zincir-Heywood had been a researcher at Sussex University, UK and
Karlsruhe University, Germany as well as working as an instructor at the
Internet Society Network Management workshops. She has published over 150
papers in network management, security , information systems and computational
intelligence fields. She has substantial experience of industrial research in
systems security and network management related topics with Raytheon, RUAG,
Gtech, Palomino, Genieknows, and Public Safety Canada. Dr. Zincir-Heywood is a
member of the IEEE and ACM.
3- Workshop
on Evolutionary Computation in Computational Structural Biology
In the last two decades, many computer
scientists in Artificial Intelligence have
made significant contributions to modeling biological systems as a means of
understanding the molecular basis of mechanisms in the healthy and diseased
cell. In particular, the field of computational structural biology is now highly
populated by researchers in evolutionary computation. Great progress is being
made by these researchers on novel and powerful
algorithms to solve exceptionally challenging computational structural biology
problems at the heart of molecular biology, such as structure prediction,
analysis, and design of biological macromolecules (proteins, RNA). These
problems pose difficult search and optimization tasks on modular systems with
vast, high-dimensional, continuous search spaces often underlined by non-linear
multimodal energy surfaces.
The focus of this workshop is the use of
nature-inspired approaches to central problems in computational structural
biology, including optimization methods under the umbrella of evolutionary
computation. A particular emphasis will be on progress in the application of
evolutionary computation to problems related to any aspects of protein
structure modeling, characterization, and analysis. The workshop will allow for
a broader focus on all structure-related problems that necessitate the design
of novel evolutionary computation approaches. These may include broader
structure modeling settings beyond de novo structure prediction, such as
mapping of protein and peptide energy landscapes, structure analysis, design,
docking, and other emerging problems in computational structural biology.
One of the objectives of this workshop is to
aid evolutionary computation researchers to disseminate recent findings and
progress. The workshop will provide a meeting point for authors and attendants
of the GECCO conference who have a current or developing interest in
computational biology. We believe the workshop will additionally attract
computational biology researchers that will further add to the attendance and
GECCO community and possibly spur novel collaborations. We hope this workshop
will stimulate the free exchange and discussion of novel ideas and results
related to structure-central problems bridging computational biology and
evolutionary computation.
Areas of interest include (but are not
restricted to):
Use of artificial life models like cellular
automata or Lindenmayer systems in the modeling of biological problems.
Study and analysis of properties of biological
systems like self-organization, emergent behavior or morphogenesis.
Multi-objective approaches in the modeling of
computational biology problems.
Use of natural and evolutionary computation
algorithms in protein structure classification and prediction (secondary and
tertiary).
Mapping of protein and peptide energy landscapes.
Modeling of temporal folding of proteins.
Protein design
Protein-ligand and protein-protein docking.
Biographies
José Santos
He obtained
an MS degree in Physics (specialization in Electronics) from the University of
Santiago de Compostela, Spain, in 1989, and a Ph.D. from the same University in
1996 (specialization in Artificial Intelligence). He is currently an Associate
Professor, accredited as Full Professor, in the Department of Computer Science
at the University of A Coru?a (Spain). His research interests include
artificial life, neural computation, evolutionary computation, autonomous
robotics and computational biology. In the last years his research was focused
on computational biology, applying all the knowledge acquired in the other
research lines to the computational modeling of biological problems.
Julia Handl
She obtained
a Bsc (Hons) in Computer Science from Monash University in 2001, an MSc degree
in Computer Science from the University of Erlangen-Nuremberg in 2003, and a
PhD in Bioinformatics from the University of Manchester in 2006. From 2007 to
2011, she held an MRC Special Training Fellowship at the University of
Manchester, and she is now a Lecturer in the Decision and Cognitive Sciences Group
at the Manchester Business School. Her research includes theoretical and
empirical work related to the development and use of data-mining and
optimization approaches in a variety of application areas including
computational biology. She has a particular interest in improving the
optimization approaches employed in fragment-assembly approaches to protein
structure.
Amarda Shehu
Shehu is an Associate Professor in the Department of
Computer Science at George Mason University. She holds affiliated appointments
in the School of Systems Biology and the Department of Bioengineering. She
received her B.S. in Computer Science and Mathematics from Clarkson University
in Potsdam, NY in 2002 and her Ph.D. in Computer Science from Rice University
in Houston, TX in 2008, where she was an NIH fellow of the Nanobiology Training
Program of the Gulf Coast Consortia. Shehu's research contributions are in
computational structural biology, biophysics, and bioinformatics with a focus
on issues concerning the relationship between biomolecular sequence, structure,
dynamics, and function. Her research on probabilistic search and optimization
algorithms for protein structure modeling is supported by various NSF programs,
including Intelligent Information Systems, Computing Core Foundations, and
Software Infrastructure. Shehu is also the recipient of an NSF CAREER award in
4- 6th Workshop on Visualisation Methods in Genetic
and Evolutionary Computation (VizGEC 2015)
VizGEC is intended to
explore, evaluate and promote current visualisation developments in the area of
genetic and evolutionary computation (GEC). Visualisation is a crucial tool in
this area, providing vital insight and understanding into algorithm operation
and problem landscapes as well as enabling the use of GEC methods on data
mining tasks. As well as allowing us to observe how individuals interact,
visualising the evolution of a synthetic genetic population over time
facilitates the analysis of how individuals change during evolution, allowing
the observation of undesirable traits such as premature convergence and
stagnation within the population.&
In addition to
visualising the solutions generated by a GEC process, we can also visualise the
processes themselves. It can be useful, for example, to investigate which
evolutionary operators are most commonly applied by an algorithm, as well as
how they are applied, in order to gain an understanding of how the process can
be most effectively tuned to solve the problem at hand.& Advances in
animation and the prevalence of digital display, rather than relying on the
paper-based presentation of a visualisation, mean that it is possible to use
visualisation methods so that aspects of an algorithm's performance can be
evaluated online.
Biographies
David Walker
Associate Research Fellow with the College of Engineering, Mathematics and
Physical Sciences at the University of Exeter.& The focus of his PhD was
the understanding of many-objective populations.& A principal component of
his thesis involved visualising such populations and he is particularly
interested in how evolutionary algorithms can be used to enhance visualisation
methods.& More recently, his research has investigated evolutionary methods
for the data mining of many-objective populations, as well as for training
artificial neural networks and designing novel nanomaterials.& His general
research interests include visualisation, evolutionary problem solving,
particularly machine learning problems, techniques for identifying preference
information in data and visualisation methods.
Richard Everson
Professor of Machine Learning at the University of Exeter.& &He has a
degree in Physics from Cambridge University and a PhD in Applied Mathematics
from Leeds University.& He worked at Brown and Yale Universities on fluid
mechanics and data analysis problems until moving to Rockefeller University,
New York, to work on optical imaging and modelling of the visual cortex. After
working at Imperial College, London, he joined the Computer Science department
at Exeter University. His research interests lie in statistical pattern
recognition, multi-objective optimisation and the links between them.&
Recent interests include the optimisation of the performance of classifiers,
which can be viewed as a many-objective optimisation problem requiring novel
methods for visualisation. Research on the construction of league tables has
led to publications exploring the multi-objective nature and methods of
visualising league tables.
Jonathan Fieldsend
Senior Lecturer in Computer Science at the University of Exeter.& &He
has a degree in Economics from Durham University, a Masters in Computational
Intelligence from the University of Plymouth and a PhD in Computer Science from
the University of Exeter.& He has held postdoctoral positions as a
research fellow (working on the interface of Bayesian modelling and
optimisation) and as a business fellow (focusing on knowledge transfer to
industry) prior to his appointment to an academic position at Exeter. His
research interests include multi- and many-objective optimisation, machine
learning and statistical pattern recognition and the interface between these
areas. Work in these fields has led to an interest in visualisation, which in
turn has led to peer reviewed work on the application and comparison of
existing visualisation techniques to new domains, and the investigation of
novel visualisation techniques. He has been active within the evolutionary
computation community as a reviewer and program committee member since 2003.
5- Evolutionary Rule-based Machine Learning
(former Int. Workshop on Leaning Classifier Systems)
Learning Classifier Systems (LCSs), introduced by John Holland [1] as a way of combining evolutionary computation with machine learning, have been widely applied from data mining to automated innovation and on-line control. LCSs have been an integral part of the field of evolutionary computation almost since its very beginnings, and so this workshop is very interesting not only for the Genetic and Evolutionary Computation (GEC) community, but also because it shares many common research topics with the broader GEC field such as linkage learning, niching techniques, variable-length representations, etc.
Scopes of interests include but are not limited to:
Paradigms of LCS (Michigan, Pittsburgh, ...)
Theoretical developments (behavior, scalability and learning bounds, ...)
Representations (binary, real-valued, oblique, non-linear, fuzzy, ...)
Types of target problems (single-step, multiple-step, regression/function ?approximation, ...)
System enhancements (competent operators, problem structure ?identification and linkage learning, ...)
LCS for Cognitive Control (architectures, emergent behaviors, ...)
Applications (data mining, medical domains, bioinformatics, intelligence in ?games ...)
Optimizations and parallel implementations (GPU, matching algorithms, ...)
Biographies
Karthik Kuber
He received his PhD in 2014 from Syracuse?University in Computer Science. His dissertation research was?on studying evolutionary algorithms from a network perspective, mainly focusing on Genetic Algorithms, Particle Swarms, and Learning Classifier Systems. He worked on information theoretic fitness measures for Learning Classifier Systems during his MS thesis, also at Syracuse. Prior to graduate school, he worked at Tata Consultancy Services in Bangalore, and received a BE in Electronics and Communication Engineering from Visvesvaraya Technological University. He is currently working at Microsoft where his interests are in exploring and applying various machine learning, analysis and modelling techniques in the context of large-scale engineering systems.
Masaya Nakata
Mr. Nakata received the
B.A. and M.Sc. degrees in informatics from the University of Electro-
Communications, Chofu, Tokyo, Japan, in 2011 and 2013 respectively. He is the
Ph.D. candidate in the University of Electro- Communications, the research
fellow of Japan Society for the Promotion of Science, Chiyoda-ku, Tokyo, Japan,
and a visiting student of the School of Engineering and Computer Science in
Victoria University of Wellington from 2014. He was a visiting student of the
Department of Electronics and Information, Politecnico di Milano, Milan, Italy,
in 2013, and of the Department of Computer Science, University of Bristol,
Bristol, UK, in 2014. His research interests are in evolutionary computation,
reinforcement learning, data mining, more specifically, in learning classifier
systems. He has received the best paper award and the IEEE Computational
Intelligence Society Japan Chapter Young Researcher Award from the Japanese
Symposium of Evolutionary Computation 2012. He is a co-organizer of
International Workshop on Learning Classifier Systems (IWLCS) for .
Kamran Shafi
Dr. Shafi holds a PhD in
computer science, a M.Sc. in telecoms engineering and a B.Sc. in electrical
engineering. Dr. Shafi is the organising member (elected) for the International
Workshop on Learning Classifier Systems (IWLCS) 2013-14 and 2015-16. He was the
chair of Computational Intelligence Day workshop held at the University of New
South Wales (UNSW-Canberra) Australia in September 2013. He was the publicity
chair for the 2012 World Congress on Computational Intelligence (WCCI 2012). He
has been a program committee member and chair/co-chair of several workshops at
GECCO and IEEE CEC conferences since 2005. His PhD thesis &An online and
adaptive signature-based approach for intrusion detection using learning
classifier systems (LCS)& received the Stephen Fester Award for the most
outstanding thesis on an information technology topic by a postgraduate
research student in the School of ITEE at UNSW Canberra. His other major
research achievements in the field of LCS research include the development of
an LCS based scenario mining approach in the context of free- flight air
traffic control concept and development of an LCS based multi-objective
hyper-heuristic framework for the defence logistics problem.
6- 5th Workshop on Evolutionary Computation for the Automated Design of Algorithms (ECADA)
How can we automatically generate
algorithms on demand? While this was one of the original aims of Machine
Learning and Artificial Intelligence in the early 1950s, and more recently
Genetic Programming in the early 1990s, existing techniques have fallen-short
of this elusive goal. This workshop will outline a number of steps in the right
direction on the path to achieving this goal. In particular, this workshop will
focus on the burgeoning field of hyper-heuristics which are meta-heuristics
applied to a i.e., any method of sampling a set of
candidate algorithms. Genetic Programming has most famously been employed to
this end, but random search and iterative hill-climbing have both also
successfully been employed to automatically design novel (components of)
algorithms.
The main objective of this workshop is
to discuss hyper-heuristics employing evolutionary computation methods for
generating algorithms. These methods have the advantage of producing solutions
that are applicable to any instance of a problem domain, instead of a solution
specifically produced to a single instance of the problem. The areas of
application of these methods include, for instance, data mining, machine
learning, and optimization.
Biographies
John R. Woodward
He is a lecturer at the
University of Stirling, within the CHORDS group (/)
and is employed on the DAASE project (), and for the
previous four years was a lecturer with the University of Nottingham. He holds
a BSc in Theoretical Physics, an MSc in Cognitive Science and a PhD in Computer
Science, all from the University of Birmingham. His research interests include
Automated Software Engineering, particularly Search Based Software Engineering,
Artificial Intelligence/Machine Learning and in particular Genetic
Programming.
He has over 50 publications
in Computer Science, Operations Research and Engineering which include both
theoretical and empirical contributions, and given over 100 talks at
International Conferences and as an invited speaker at Universities. He has
worked in industrial, military, educational and academic settings, and been
employed by EDS, CERN and RAF and three UK Universities.
Daniel R. Tauritz
He is an Associate
Professor in the Department of Computer Science at the Missouri University of
Science and Technology (S&T), on sabbatical at Sandia National Laboratories
academic year, a former Guest Scientist at Los Alamos
National Laboratory (LANL), the founding director of S&T's Natural
Computation Laboratory (), and founding
academic director of the LANL/S&T Cyber Security Sciences Institute. He
received his Ph.D. in 2002 from Leiden University for Adaptive Information
Filtering employing a novel type of evolutionary algorithm. He served
previously as GECCO 2010 Late Breaking Papers Chair, COMPSAC 2011 Doctoral
Symposium Chair, GECCO 2012 GA Track Co-Chair, and GECCO 2013 GA Track
Co-Chair. For several years he has served on the GECCO GA track program
committee, the Congress on Evolutionary Computation program committee, and a
variety of other international conference program committees. His research
interests include the design of hyper-heuristics and self-configuring
evolutionary algorithms and the application of computational intelligence
techniques in cyber security, critical infrastructure protection, and
search-based software engineering. He was granted a US patent for an
artificially intelligent rule-based system to assist teams in becoming more
effective by improving the communication process between team members.
Manuel López-Ibá?ez
López-Ibá?ez is a
postdoctoral researcher (Chargé de recherche) of the Belgian Fund for
Scientific Research (F.R.S.-FNRS) working at the IRIDIA laboratory of
Université libre de Bruxelles, Brussels, Belgium. He received the M.S. degree
in computer science from the University of Granada, Granada, Spain, in 2004,
and the Ph.D. degree from Edinburgh Napier University, U.K., in 2009. He has
published 13 journal papers, 6 book chapters and 33 papers in peer-reviewed
proceedings of international conferences on diverse topics such as evolutionary
algorithms, ant colony optimisation, multi-objective optimisation, and various
combinatorial and real-world optimisation problems. His current research
interests are experimental analysis, automatic configuration and automatic
design of optimisation algorithms, for single and multi-objective optimisation.
He is the lead developer and current maintainer of the irace automatic
configuration method ().
7- Workshop
on Evolutionary Computation Software Systems (EvoSoft)
Evolutionary computation (EC) methods are applied in many
different domains. Therefore soundly engineered, reusable, flexible,
user-friendly, and interoperable software systems are more than ever required
to bridge the gap between theoretical research and practical application.
However, due to the heterogeneity of the application domains and the large
number of EC methods, the development of such systems is both, time consuming
and complex. Consequently many EC researchers still implement individual and
highly specialized software which is often developed from scratch, concentrates
on a specific research question, and does not follow state of the art software
engineering practices. By this means the chance to reuse existing systems and
to provide systems for others to build their work on is not sufficiently seized
within the EC community. In many cases the developed systems are not even
publicly released, which makes the comparability and traceability of research
results very hard.
This workshop enables EC researchers to exchange their
ideas on how to develop and apply generic and reusable EC software systems and
to present open and freely available solutions on which others can build their
work on. Furthermore, the workshop should help to identify common efforts in
the development of EC software systems and should highlight cooperation
potentials and synergies between different research groups. It concentrates on
the importance of high-quality software systems and professional software
engineering in the field of EC and provides a platform for EC researchers to
discuss the following and other related topics:
development and application of generic and reusable EC
software systems
architectural and design patterns for EC software
software modeling of EC algorithms and problems
open-source EC software systems
expandability, interoperability, and standardization
comparability and traceability of research results
graphical user interfaces and visualization
comprehensive statistical and graphical results
parallelism and performance
usability and automation
comparison and evaluation of EC software systems
Biographies
Stefan Wagner
his MSc in computer science in 2004 and his PhD in technical sciences in 2009,
both from the Johannes Kepler University Linz, Austria. From 2005 to 2009 he
worked as an associate professor for software project engineering and since
2009 as a full professor for complex software systems at the University of
Applied Sciences Upper Austria, Campus Hagenberg, Austria. Dr. Wagner is one of
the founders of the research group Heuristic and Evolutionary Algorithms Laboratory
(HEAL) and is the project manager and head developer of the HeuristicLab
optimization environment.
Affenzeller
He has published several
papers, journal articles and books dealing with theoretical and practical
aspects of evolutionary computation, genetic algorithms, and meta-heuristics in
general. In 2001 he received his PhD in engineering sciences and in 2004 he
received his habilitation in applied systems engineering, both from the
Johannes Kepler University Linz, Austria. Michael Affenzeller is professor at
the University of Applied Sciences Upper Austria, Campus Hagenberg, and head of
the research group Heuristic and Evolutionary Algorithms Laboratory (HEAL).
8- Black Box Optimization Benchmarking 2015 (BBOB 2015)
Benchmarking of optimization
algorithms is crucial to assess performance of optimizers quantitatively,
understand weaknesses and strengths of each algorithm and is the compulsory
path to test new algorithm designs. The black-box-optimization benchmarking
workshop aims at benchmarking both stochastic and deterministic continuous
optimization algorithms in an anytime scenario for (i) unconstrained
optimization problems and (ii) possibly in expensive settings where only a
limited budget is affordable (e.g. (meta-)model assisted algorithms).
Biographies
Youhei Akimoto
assistant professor at Shinshu University, Japan. He received his diploma
(2007) in computer science and his master degree (2008) and PhD (2011) in
computational intelligence and systems science from Tokyo Institute of
Technology, Japan. He was a research fellow of Japan Society for the Promotion
of Science for one year () at Tokyo Institute of Technology.
Afterwords, he was a post-doctoral research fellow at INRIA Saclay
Ile-de-France () and started working at Shinshu University in April
2013. His research interests include design principles and theoretical analysis
of stochastic search heuristics, especially the Covariance Matrix Adaptation
Evolution Strategy.
Anne Auger
permanent researcher at the French National Institute for Research in Computer
Science and Control (INRIA). She received her diploma (2001) and PhD (2004) in
mathematics from the Paris VI
University. Before to join INRIA, she worked for two years ()
at ETH in Zurich. Her main research interest is stochastic continuous
optimization including theoretical aspects and algorithm designs. She is a
member of ACM-SIGECO executive committee and of the editorial board of
Evolutionary Computation. She has been organizing the biannual Dagstuhl seminar
&Theory of Evolutionary Algorithms& in 2008 and 2010 and the BBOB
workshops in , 2012, and 2013.
Dimo Brockhoff
He received
his diploma in computer science from University of Dortmund, Germany in 2005
and his PhD (Dr. sc. ETH) from ETH Zurich, Switzerland in 2009. Afterwards, he
held two postdoctoral research positions in France at INRIA Saclay
Ile-de-France () and at Ecole Polytechnique (). Since
November 2011, he has been a permanent researcher at INRIA Lille - Nord Europe,
France. His research interests are focused on evolutionary multiobjective
optimization (EMO), in particular on theoretical aspects of indicator-based
search and on the benchmarking of blackbox algorithms in general. Dimo already
served as co-organizer of the BBOB workshop in 2013.
Nikolaus Hansen
research scientist at INRIA, France. Educated in medicine and mathematics, he
received a Ph.D. in civil engineering in 1998 from the Technical University
Berlin under Ingo Rechenberg. Before he joined INRIA, he has been working in
evolutionary computation, genomics and computational science at the Technical
University Berlin, the InGene Institute of Genetic Medicine and the ETH Zurich.
His main research interests are learning and adaptation in evolutionary
computation and the development of algorithms applicable in practice. His
best-known contribution to the field of evolutionary computation is the
so-called Covariance Matrix Adaptation (CMA).
Olaf Mersmann
He recieved
his BSc and MSc in Statistics from the TU Dortmund. He is currently pursuing a
PhD in Statistics (expected in early 2015) with work based on his Bachelor
Thesis on the design and analysis of benchmark experiments. Part of this work
has been presented at conferences and is currently under review for
publication. Using statistical and machine learning methods on large benchmark
databases to gain insight into the structure of the algorithm choice problem is
one of his current research interests. Olaf already co-organized the BBOB
workshop in 2010 and 2012.
Petr Po?ik
received his
Diploma degree in Technical Cybernetics in 2001 and Ph.D. in Artificial
Intelligence and Biocybernetics in 2007, both from the Czech Technical
University in Prague, Czech Republic. From 2001 to 2004 he also worked as
statistician, analyst and lecturer for StatSoft, Czech Republic. Since 2005 he
works as a researcher in the Intelligent Data Analysis Lab, Department of
Cybernetics at the Czech Technical University. Being on the boundary of
optimization, statistics and machine learning, his research interests are aimed
at improving the characteristics of evolutionary algorithms with techniques of
statistical machine learning. He also serves as a reviewer for several journals
and conferences in the evolutionary-computation field.
Student workshop
The goal of the Student Workshop is to
support students’ first research and facilitate their inclusion in the field of
Evolutionary Computation. Students will receive valuable feedback on the
quality of their work and their presentation style. This will be assured by
constructive discussions after each talk led by a mentor panel of established
researchers. Students are encouraged to use this opportunity also to get
guidance regarding future research directions. In addition, the contributing
students are invited to present their work as a poster at the GECCO 2015 Poster
Session - an excellent opportunity to discuss their work with a broader
audience and to network with academic as well as industrial members of the
community. Last, but not least, the best contributions will compete for a Best
Student Paper Award.
Biographies
She is a research
assistant at the Department of Intelligent Systems at the Jo?ef Stefan
Institute in Ljubljana, Slovenia. She received her PhD degree from the Jo?ef
Stefan International Postgraduate School in 2014. Her research interests
include evolutionary algorithms for singleobjective and multiobjective
optimization with applications in optimization of metallurgical production
processes and design of alternative energy supply systems, and machine learning
methods for text processing and outlier detection. Recently, she has been
researching visualization techniques for viewing multidimensional Pareto front
approximations found by multiobjective optimizers.
Boris Naujoks
professor for Applied Mathematics at Cologne University of Applied Sciences
(CUAS). He joint CUAs directly after he received his PhD from Dortmund
Technical University in 2011. During his time in Dortmund, Boris worked as a
research assistant in different projects and gained industrial experience
working for different SMEs. Meanwhile, he enjoys the combination of teaching
mathematics as well as computer science and exploring EC and CI techniques at
the Campus Gummersbach of CUAS. He focused on multiobjective (evolutionary)
optimization, in particular hypervolume based algorithms, and the (industrial)
applicability of the explored methods.
10- Evolving Collective Behaviors in Robotics
This workshop brings together
researchers interested in the automatic design of coordinated behaviors in
decentralized collective systems, putting the emphasis on evolutionary robotics
techniques. The goal of this workshop is to provide an updated perspective of
this field, both from a theoretical and practical perspective, and to consider
different areas of applicability for such techniques including design for
engineering and modelling for biology. Moreover, this workshop will encourage
collaboration between researchers already present at GECCO, or in other similar
venues such as the Artificial Life conferences, which are not always present at
the same conference.
Biographies
Abraham Prieto Garcia
He is an Associate
Professor at the University of A Coru?a, Spain. He is a member of the Integrated
Group for Engineering Research (GII) of the same university and leads the
Collective Systems Section within the GII. He graduated in 2002 and obtained
his Master Degree in 2004 in Industrial Engineering. In 2009 he obtained a
Magna Cum Laude for his PhD Thesis in the field of optimization techniques for
distributed problems in engineering. He started his collaboration with the GII
in 2004 developing projects related with Intelligent Processing of images and
signals and with the optimization of distributed systems. In 2005 he became
Assistant Professor and then in 2010 he gained the Associate Professor
position. Regarding his research work he is author of several papers in
journals, international conferences and book chapters. He has participated in
numerous national and regional research projects from public calls, many of
them in collaboration with private companies. His research covers the following
fields: bio-inspired techniques for distributed problems, evolutionary robotics
and image and signal intelligent processing.
Nicolas Bredeche
He is Professeur des
Universites (Professor) at Universite Pierre et Marie Curie (UPMC, Paris,
France), His research is done in the team Architectures and Models for
Adaptation and Cognition, within the Institute of Intelligent Systems and
Robotics (ISIR, CNRS). His field of research is mostly concerned with
Evolutionary Computation and Complex Systems (self-adaptive collective robotic
systems, generative and developmental systems, evolutionary robotics). In
particular, part of his work is about (a) evolutionary design and/or adaptation
of group of embodied agents and (b) artificial ontogeny such as multi-cellular
developmental systems and self-regulated networks.
Nicolas Bredeche is author of more than
30 papers in journals and major conferences in the field. He has (or currently
is) advisor or co-advisor of six PhD students and has served in program
committees and/or as track chair of the major conferences in the field of
Evolutionary Computation (incl. GECCO track chair for the Artificial Life and
Robotics track ). He is also a member of the french Evolution
Artificielle association and has been regularly co-organizing the french
Artificial Evolution one-day seminar (JET) since 2009. He has also organized
several international workshops in Evolution, Robotics, and Development of
Artificial Neural Networks.
Evert Haasdijk
He is assistant professor
in the Computational Intelligence group at VU. He has been with the
computational intelligence group at VU since 2008, researching on-line
evolution in robots. Before that, he was research assistant at Tilburg
University, researching social learning in populations of software agents. Dr
Haasdijk has ample experience in evolutionary computation, stretching back to
the successful PAPAGENA project in 1992, where he participated as an industry
partner. He has served as member of program committees of well-established
conferences in the field of evolutionary computation (CEC, GECCO), was local
chair for GECCO 2013 and (co-)organised various workshops and track such as the
EvoROBOT track at EvoSTAR conferences and the International Workshop on the
Evolution of Physical Systems at ECAL and ALIFE conferences. Dr Haasdijk was
guest editor for the Special Issue on Evolutionary Robotics of the Evolutionary
Intelligence journal and invited speaker at the PPSN XIII Workshop on
Nature-Inspired Techniques for Robotics.
11- Women@GECCO
Workshop: Sunday July 12,
16:10-18:00
Sunday July 12, 18:00 - 19:30
Women form an under-represented cohort in evolutionary
computation, whether the cohort is examined in industry, academics or both. The
broad objective of this workshop is bring women attending GECCO together to
share ways that will generate, encourage and support academic, professional and
social opportunities for women in evolutionary computation.
The workshop will foster, sustain and impart
role models and offer the opportunity to interact with others &in the same boat&.
We encourage all faculty, professional and students interested in Evolutionary
Computation who identify as female, who consider themselves underrepresented
minorities with similar issues, or are male and supportive of the issues to
Introduction of Workshop and Participants
Invited talk by Emma Hart on &Lifelong Learning: An Academic &
Personal Perspective& (please find details below)
Open Discussion
Science Slam: short performances of our 5 selected speakers: Tea Tusar,
Madalina Drugan, Julia Handl, Amarda Shehu, and Arina Buzdalova
&Poster Session& (please find details below)
*Invited Talk*
Learning: An Academic &
Perspective &- &Emma Hart
My current research focuses on
developing algorithms that continuously learn
and improve through
the experience
gained from solving many problems over time. In this talk, I will discuss some
of the scientific ideas behind this research, but also describe the process of
arriving at this point in my academic life, through a journey that has involved
life-long learning on my own part, moving from Chemistry to Evolutionary
Computing to Artificial Immune Systems to something that brings together all
three fields in naby
gained a 1st Class Honours Degree in Chemistry
from the University of Oxford, followed by an MSc in Artificial Intelligence
from the University of Edinburgh in 1996. Her PhD, also from the University of
Edinburgh, explored the use of immunology as an inspiration for computing,
examining a range of techniques applied to optimisation and data classification
She moved to Edinburgh Napier University in 2000 as a
lecturer, and was promoted to a Chair in 2008 in Natural Computation. She leads
the Centre for Algorithms, Visualisation and Evolving Systems with the
Institute for Informatics&
Innovation at Edinburgh Napier. Her research focuses on the development of
novel bio-inspired techniques for solving a range of real-world optimisation
and classification problems, as well as exploring the fundamental properties of
immune-inspired computing through modelling and simulation. Her current
research interests are focused on systems that can continue learning over their
lifetime, with applications in optimisation and robotics. This brings together
keys ideas from the AIS and Evolutionary Computing communities. In addition to
academic research, she is also involved in Knowledge Transfer and Commercial
activities, applying her research to real problems in industry.
* Open Discussion*
Our workshops have recently also included an open
discussion on issues reflective of the community, such as:
What will help women in evolutionary computation remain
in the field long term?
What are the different challenges along a career path?
What strategies will help women navigate career and
family responsibilities?
What changes can be adopted by women as a group, by our
larger community with respect to our conferences and awards, or by our academic
institutions with respect to positions and promotions?
Are there experiences and strategies that can be shared
which allow senior women to support more junior ones or peers to support each
What can women in EC do to help each other&s isolation
because of under-representation?
*Science Slam*
Short performances of our 5 selected speakers: Tea Tusar, Madalina Drugan,
Julia Handl, Amarda Shehu, and Arina Buzdalova, who will talk about their
research in a creative and non-standard way.
*Poster Session*
We invite all participants to bring along material to introduce themselves
(e.g., a poster or a printout of one or two slides, but feel free to bring
other items such as pictures or paintings, the topic is entirely up to you (we
suggest to have some details about your research ambitions/future or completed
projects/... but feel free to add some comments about your private/personal
situation if you are happy to share these things). This interactive session
will allow us to get to know each other better. Please do not overload your
poster/picture/... as time for the presentation will be limited. Please be aware that the posters might be visible to general GECCO attendees.
So you should keep this in mind and only add things you are comfortable
Use this opportunity to present your work in an open, enthusiastic, and
welcoming environment.
Let us know which topics motivate your work and share with us your progress on
this journey as well as open questions arising from your work. The poster
session is a great opportunity to connect to fellow researchers in evolutionary
computation. Take advantage and get useful feedback on your work. More
importantly, make yourself and your research topics known!
*Panel Discussion *
Sunday July 12, 18:00 - 19:30
We started a &conversation& on work/life
balance at the panel last year. This year, we want to continue that
&conversation& and dive into discussing how each one of us work to
combine a successful career with a rich private life. Because a balanced life
is something that looks different for everyone, we want to hear from you:
what makes you feel like your life is in balance or
out of balance?
what takes up most of your time?
do you feel anything is lacking?
what are the challenges at work?
what would you like to see changing?
This year's work/life balance panel encourages everyone
to join us and take a more active role in our panel.
We want to invite everyone at different
stages of their career from students, to early career participants, to more
senior ones! If you have any topics that you would like to see discussed in
this panel, please do not hesitate to contact the organizers Emily Dolson , Anya E. Johnson ,
and Nur Zincir-Heywood.
*Your Participation*
No submission is required to attend this quarter-day workshop however you
should indicate your attendance at GECCO registration. Participants are
strongly encouraged to bring along material for the poster session.& For
more information, contact including on the subject line: WOMEN@GECCO.
Carola Doerr
is a permanent researcher with the CNRS and the Université Pierre et Marie
Curie (Paris 6). She studied mathematics at Kiel University (Diploma in 2007)
and computer science at the Max Planck Institute for Informatics and Saarland
University (PhD in 2011). From Dec. 2007 to Nov. 2009, Carola Doerr has worked
as a business consultant for McKinsey & Company, mainly in the area of
network optimization. She was a post-doc at the Université 7 in Paris and the
Max Planck Institute for Informatics in Saarbrücken. Carola Doerr's main
research interest is in the theory of randomized algorithms, both in the design
of efficient algorithms as well as in randomized query complexities. She has
published several papers in the field of evolutionary computation.
Anna Esparcia
Affiliation: Universitat Politècnica de València, Spain
Anna has the role of vice chair of the Women@GECCO group. She is chair of GECCO
2015 so will take a modest role this year in organizating the meeting.
Gabriela Ochoa
Affiliation: Computing Science and Mathematics, School of
Natural Sciences, University of Stirling, Scotland.
Gabriela Ochoa is a Lecturer in Computing Science
at the University of Stirling in Scotland. Her research interests lie in the
foundations and application of evolutionary algorithms and heuristic search methods,
with emphasis on autonomous (self-*) search and fitness landscape analysis. She
has published over 70 international peer reviewed papers. She is associate
editor of Evolutionary Computation (MIT Press), was involved in founding the
Self-* Search track at GECCO, co-chaired EvoCOP 2014 and has organised several
special sessions at international conferences. She serves as secretary of the
Women@GECCO group.
Affiliation:
Massachusetts Institute of Technology
Una-May is a Fellow of the International Society of Genetic and Evolutionary
Computation, now ACM Sig-EVO.
she received the EVO-Star award recognizing her contributions to evolutionary
computation. At MIT CSAIL, Una-May leads the AnyScale Learning For All (ALFA)
research group.
She has chaired or
co-chaired GECCO, EuroGP and GPTP. She serves as vice-chair of ACM SIGEVO, the
area editor for Data Analytics and Knowledge Discovery for Genetic Programming
and Evolvable Machines, an editorial board member of Evolutionary Computation,
and action editor for the Journal of Machine Learning Research. In 2013, with
Anna Esparcia, Anniko Ekart and Gabriela Ochoa she inaugurated the Women@GECCO
meeting and chairs the group.
Zincir-Heywood
Zincir-Heywood is a Professor of Computer Science at Dalhousie University,
Canada. She received her PhD in 1998 in Computer Science and Engineering from
Ege University, Turkey. Prior to moving to Dalhousie in 2000, Dr.
Zincir-Heywood was a researcher at Sussex University, UK and Karlsruhe
University, Germany as well as working as an instructor at the Internet Society
Network Management workshops. She has published over 150 papers in network
management, security, information systems and computational intelligence
fields. She has substantial experience of industrial research in systems
security and network management related topics with Raytheon, RUAG, Gtech,
Palomino, Genieknows, and Public Safety Canada. Dr. Zincir-Heywood is a member
of the IEEE and ACM.
is a Birmingham Fellow and Lecturer in the School of Computer Science at the
University of Birmingham, UK. She received her degree and PhD from the TU
Dortmund, Germany, in 2007 and 2011, respectively. Afterwards, she held a
postdoctoral research position at the University of Warwick, UK. Her PhD topic
was &Theoretical Foundations of Artificial Immune Systems& and her
current research focuses on the theoretical analysis of all kinds of randomised
search heuristics. She is also interested in computational and theoretical
aspects of immunology. She has given tutorials on &Artificial Immune
Systems for Optimisation& at previous GECCOs and was co-chair of the AIS
track at GECCO 2014. She is member of the editorial board of Evolutionary Computation
(MIT Press) and co-organiser of FOGA 2015.
key contributors are Leigh Sheneman,
Whitlock, and Emilia Tantar.
12- 2nd Workshop on Metaheuristic Design Patterns (MetaDeeP)
Over many decades, Evolutionary Computation (and meta-- and
hyper--heuristics in general) has flourished, spawning an enormous variety of
algorithms, operators and representations. However, metaheuristics
research now requires a higher-level architectural and unifying perspective.
There is a pressing need to:&
ground `loosely-specified'
(e.g. metaphorically-inspired) approaches in terms of well-defined framew&
achieve greater automation of
metaheuristic and and
facilitate large-scale
knowledge discovery across frameworks and problem domains.
The software industry has already evolved
to meet similar challenges, capturing recurring cross-cutting concerns via
structured heuristics known as `Design Patterns'. Following the
introduction of the seminal design patterns catalogue by the &gang of four&
[1], the default level of design discourse among software practitioners
significantly increased, and today patterns such as &Factory Method& or
&Observer& are software engineers& lingua franca. The workshop organizers
strongly believe that the EC/metaheuristics community needs and deserves a
corresponding breakthrough. The vision for framing such Metaheuristic Design
Patterns (MDP) has been advocated in a recent lecture [2]; similar desires have
also been expressed in [3]. GECCO 2013 saw the highly successful first workshop
on MDP where MDPs such as &Template Method Hyper-Heuristics& and &Candidate
Solution Repair& were proposed, and the notion of pattern languages was
discussed.
The goal of this second workshop on MDP is to continue to
provide a forum for those interested in contributing to the MDP vision and/or
willing to demonstrate its usefulness in practical and theoretical studies. We
would emphasize that we see the workshop as distinctly bottom--up, driven by
ideas and needs of the community. Suggestions for further MDPs are welcome as
we seek to ground old and new ideas and best practices into an emerging
catalogue for MDPs. Also, building on pattern languages for software design
(e.g. [4],[5]), we welcome proposals for pattern languages suitable for
characterising meta-heuristic design patterns. Finally, we would welcome
suggestions for &executable heuristic& patterns in an attempt to significantly
move the level of meta-heuristic automation forward.
By realizing this vision via the second
MDP workshop, we hope to see it adopted by a large part of community and thus
help to advance our domain as a whole.
Erich Gamma,
Richard Helm, Ralph Johnson and John Vlissides. Design Patterns: Elements of Reusable Object-Oriented Software, Addison-Wesley, 1995.
Jerry Swan.
Metaheuristic Design Patterns. Invited lecture at the Workshop on Evolutionary
Computation for Automatic Design of Algorithms, GECCO& 2013.
[3] Natalio
Krasnogor.&Handbook
of Natural Computation, chapter &Memetic Algorithms&. Natural
Computing. Springer Berlin / Heidelberg, 2009.
[4] Pattern
Languages of Programs Conference,
[5] European Conference on
Pattern Languages of Programs,
Biographies
Chris Simons
He spent many years as an industrial software development practitioner in a
variety of roles including technical architect, agile development methodology
consultant and trainer. Now a senior lecturer, his research interests lie in
human-centred bio-inspired metaheuristics and Search-Based Software Engineering
Jerry Swan
entering academia,
spent 20 years in industry as a systems architect
and software company owner. His research include meta- and hyper-heuristics,
symbolic computation and machine learning. He has published more than 50 papers
in international journals and conferences. Jerry has lectured and presented his
research worldwide, and has been running international workshops and tutorials on
the automated&design&of&metaheuristics since 2011.
Krzysztof Krawiec
(Chris) Krawiec is an associate professor at Poznan University of Technology,
Poland. He published over 70 papers on genetic programming, semantics in GP,
modularity and coevolution, co-chaired EuroGP’13 and EuroGP'14, and is an
associate editor of Genetic Programming and Evolvable Machines journal.
Daniel Tauritz
He is an Associate Professor of Computer Science at the Missouri
University of Science and Technology (S&T). He served previously as GECCO
2010 Late Breaking Papers Chair and GECCO 2012 & 2013 GA Track Co-Chair.
His research interests include the design of hyper-heuristics and
self-configuring evolutionary algorithms and the application of computational
intelligence techniques in cyber security, critical infrastructure protection,
and search-based software engineering.
He has been researching meta-heuristics since 1994. &He has published
extensively on formalisms of metaheuristic components and design patterns,
especially for adaptive and self-adaptive evolutionary and memetic systems.
14- Semantic Methods in Genetic Programming (SMGP)
Genetic programming (GP) — the application of evolutionary computing
techniques to the creation of computer programs — has been a key topic in
computational intelligence in the last couple of decades. In the last few years
a rising topic in GP has been the use of semantic methods. The aim of this is
to provide a way of exploring the input-output behaviour of programs, which is
ultimately what matters for problem solving. This new approach has produced
substantially better results on a number of problems, both benchmark problems
and real-world applications and, has been grounded in a body of theory, which
also informs algorithm design and builds interesting links with theoretical
computer science and search-based software engineering. There are a number of
research groups that are active in this area around the world. This is a
growing research area, with an increasing number of publications each year.
This workshop is the second edition after the highly successful
event we organized at PPSN’14, which attracted 30+ participants for an entire
day. It provides both an opportunity to consolidate and extend work in this
growing area, and to inform a wider group of people about this growing area of
work. We can see these semantic methods being important in other areas of
computational intelligence and machine learning, and so this provides a good
opportunity for a broader set of conference participants to learn about this
growth area.
information:
Biographies
Colin Johnson
He is a Reader in the School of Computing at
the University of Kent. He has been active in bio-inspired computing research
for the last 15 years, and in recent years has been particularly focused on
genetic programming, with a substantial publication record in the area.
He has been active in conferences within the
computational intelligence area, including membership of the programme
committee for a number of conferences in the area, and would bring this
experience to the organisation of this workshop.
Krzysztof Krawiec
He is an associate professor in the Institute of Computing Science,
Poznan University of Technology, Poland, pursuing research in several branches
of computational intelligence, primarily evolutionary computation, machine
learning, and pattern recognition. He has been publishing in the GP field for
about 13 years, and since 2008 he is actively developing various GP methods
that involve program semantics. He served as a co-chair of the European
Conference of Genetic Programing (EuroGP) in 2012 and 2013, and is an associate
editor of Genetic Programming and Evolvable Machines journal.
Alberto Moraglio
He is a Lecturer in Computer Science in the
College of Engineering, Mathematics and Physical Sciences at the University of
Exeter, UK. He has been active in bio-inspired computing and genetic
programming research for the last 10 years with a substantial publication
record in the area.& He is the founder of the Geometric Theory of
Evolutionary Algorithms, which unifies Evolutionary Algorithms across representations
and has been used for the principled design of new successful search
algorithms, including a new form of Genetic Programming based on semantics, and
for their rigorous theoretical analysis. He was co-chair of the European
Conference on Genetic Programming 2012 and 2013, and has
regular&tutorials&at GECCO and IEEE CEC. He is a member of the
editorial board for Genetic Programming and Evolvable Machines (Springer).
Michael O’Neill
He is the ICON Chair of Business Analytics in
the UCD School of Business, is a founding Director of the UCD Natural Computing
Research & Applications group, and is Director of the UCD Complex &
Adaptive Systems Laboratory (The CASL Institute). He has published in excess of
250 peer-reviewed publications. Michael was Local Chair of GECCO 2011, which
was held in Dublin.
In the past he has
served as Chair of the Genetic Programming Track (GECCO 2010), Chair of the
Real World Applications Track (GECCO 2009), and was also Chair of the Grammatical
Evolution Workshops (GEWS ), and Chair of the SIGEVO Graduate Student
Workshop 2005. He has co-authored a number of successful funding applications
with a total value over EUR9 Million. In recent years his team has conducted
research focusing on syntax and semantics in genetic programming.
16- Medical Applications of Genetic and Evolutionary Computation (MedGEC)
MedGEC is the GECCO Workshop on the application
of genetic and evolutionary computation (GEC) to problems in medicine and
healthcare. A dedicated workshop at GECCO provides a much needed focus for
medical related applications of EC, not only providing a clear definition of
the state of the art, but also support to practitioners for whom GEC might not
be their main area of expertise or experience.
Biographies
Stephen L. Smith
He received
a BSc in Computer Science and then an MSc and PhD in Electronic Engineering
from the University of Kent, UK. He is currently a reader in the Department of
Electronics at the University of York, UK. Stephen's main research interests
are in developing novel representations of evolutionary algorithms particularly
with application to problems in medicine. Stephen is associate editor for the
journal Genetic Programming and Evolvable Machines and a member of the
editorial board for the International Journal of Computers in Healthcare and
Neural Computing and Applications. He has some 75 refereed publications, is a
Chartered Engineer and a fellow of the British Computer Society.
Stefano Cagnoni
He graduated
in Electronic Engineering at the University of Florence in 1988 where he has
been a PhD student and a post-doc until 1997. In 1994 he was a visiting
scientist at the Whitaker College Biomedical Imaging and Computation Laboratory
at the Massachusetts Institute of Technology. Since 1997 he has been with the University
of Parma, where he has been Associate Professor since 2004. He has been
Editor-in-chief of the &Journal of Artificial Evolution and
Applications& from 2007 to 2010. Since 1999, he has been chairman of
EvoIASP, an event dedicated to evolutionary computation f