Genetic Algorithms Digest Tuesday, Dec 22, 1998 Volume 12 : Issue 23 - Do NOT send email or reply to gadistr@aic.nrl.navy.mil - Send submissions (articles) to GA-List@aic.nrl.navy.mil - Send administrative requests (subscribe, unsubscribe, change of address, etc.,) to GA-List-Request@aic.nrl.navy.mil ********************************************************************** You can access back issues, GA code, conference announcements, etc., either through the WWW at URL http://www.aic.nrl.navy.mil/galist/ or through anonymous ftp at ftp.aic.nrl.navy.mil [132.250.84.25] in /pub/galist. ********************************************************************** Today's Topics: - GA Digest moderators' note - Phylogeny inference by GA - summary - Large NLP global optimization by GA (request help) - Fellowship in Nature-Inspired Computing R&D - Reminder, CEC99 Deadline Jan 15, 1999 - CFP: The First NASA/DOD Workshop on Evolvable Hardware - CFP: MENDEL'99 - CFP: Evolutionary Computation in Medicine - GECCO-99 Workshops ---------------------------------------------------------------------- CALENDAR OF GA-RELATED ACTIVITIES: (with GA-List issue reference) Intl Conf on Evol Computation in Engin, Chennai, India (v12n1) Jan 6-9, 99 CF99 Computational Finance, New York, NY (v12n10) Jan 6-8, 99 CIMCA99 Comp Intell for Mod Cont and Aut, Vienna, Aust (v12n10) Feb 17-19, 99 SAC99 14th Annual ACM Symposium on Applied Computing (v12n7) Feb 28-Mar 2, 99 CIMAF99 Symposium on Artificial Intelligence (v12n5) Mar 22-26, 99 SPIE Applications and Sci of Comp Intell, Orlando, FL (v12n10) Apr 5-9, 99 AISB Symp. on Creative Evol. Systems, Edinburgh, UK (v12n19) Apr 6-9, 99 ICANNGA99 Int Conf on NNs and GAs, Portoroz, Slovenia (v12n21) Apr 6-9, 99 EuroGP99 2nd Euro Workshop on GP, Goteborg, Sweden (v12n20) May 26-27, 99 EvoIASP99 1st Euro WS on EC in Image Anal & Sig Proc (v12n18) May 28, 99 EuroEctel99 1st Euro Workshop on EC in Telecommunicati (v12n16) May 29, 99 SOCO99 Soft Computing, Genova, Italy (v12n8) Jun 1-4, 99 ISAMA99 Int Soc for Arts, Math and Arch, Spain (v12n21) Jun 7-11, 99 MENDEL99 5th Int Mendel Conf on Soft Comp, Czech Rep (v12n23) Jun 9-12, 99 TAINN99 8th Turkish Symposium on AI and Neural Nets (v12n17) Jun 23-25, 99 CEF99 EC in Economics and Finance, Chestnut Hill, MA (v12n21) Jun 24-26, 99 ICML99 16th Int Conf on Mach Learning, Bled, Slovenia (v12n21) Jun 27-30, 99 CEC99 Congress on Evol Computation, Washington, DC (v12n9) Jul 6-9, 99 GECCO99 Genetic & Evol Computation Conf, Orlando, FL (v12n8) Jul 13-17, 99 AAAI99 16th National Conference on AI, Orlando, FL (v12n21) Jul 18-22, 99 EH99 1st NASA/DOD WS on Evol Hardware, Pasadena, CA (v12n23) Jul 19-21, 99 IJCAI99 WS on Agents Learning About, From, and With Ot (v12n22) Aug 2, 99 ECAL99 5th Euro Conf on Artificial Life, Lausanne, Swi (v12n20) Sep 13-17, 99 RSFDGrC99 7th Int WS Rough Sets, Fuzzy Sets, Data Min (v12n22) Nov 9-11, 99 IAT99 Intelligent Agent Technology, Hong Kong (v12n21) Dec 15-17, 99 Send announcements of other activities to GA-List@aic.nrl.navy.mil. ------------------------------ Date: Tue, 22 Dec 1998 From: The Moderators Subject: GA Digest moderators' note This issue of GA Digest concludes Volume 12. GA Digest will resume with Volume 13 in January. We would like to wish everyone in the evolutionary computation community a happy new year. Mitch Potter and Annie Wu ------------------------------ Date: Fri, 11 Dec 1998 11:55:46 +0200 From: Ariel Fligler Subject: Phylogeny inference by GA - summary Greetings, Thanks for everyone who helped me with references to GA in the domain of evolutionary trees. Here, I summarize all the references I got, in case someone else is interested: 1) Lewis, Paul O. A genetic algorithm for maximum likelihood phylogeny inference using nucleotide sequence data. Molecular Biology and Evolution 15 (3): 277-283. 2) Using Genetic Algorithms for the Construction of Phylogenetic Trees: Application to G-Protein coupled Receptors Sequences. T.H. Reijmers, R. Wehrens, F.D. Daeyaert, P.J. Lewi, and L.M.C. Buydens, BioSystems, 49, 31-43 (1999). 3) Construction of Phylogenetic Trees from Amino Acid Sequences using Genetic Algorithms. H. Matsuda, Proceedings of Genome Informatics Workshop 1995, Universal Academy Press, Tokyo, p. 19-28 (1995). Happy holidays, Ariel Fligler. ------------------------------ Date: Fri, 11 Dec 1998 19:26:26 +0800 From: Liu Hongqian Subject: Large NLP global optimization by GA (request help) Dear my friends: I am a Ph.D. student on process system engineering! I am facing a rather difficult NLP problem. In this NLP problem, there are a lot of non-equality constraints; I must search for the global optimization solution. How could I effectively process the boundary examination to factors? If possible, please help me and mail me the source code written in C/C++. I am looking forward your mail. Liu Hongqian Campus box 49# BUCT Beijing 100029 P. R. China E-mail: liuhq@mailserv.buct.edu.cn ------------------------------ Date: Wed, 16 Dec 1998 11:38:11 +0000 (GMT) From: marks@info.bt.co.uk (Mark Shackleton) Subject: Fellowship in Nature-Inspired Computing R&D Fellowship in Nature-Inspired Computing Research & Development at BT Labs The Future Technologies Research Group, part of the Applied Research and Technology (ART) department at BT Laboratories, is carrying out leading research and development into biologically inspired computing, new approaches to computation, evolutionary computing, etc. Browse http://www.labs.bt.com/projects/ftg for more details. I am keen to hear from candidates who may be interested in joining one of the company's cutting edge research groups which has a remit of carrying out world-class R&D and successful exploitation in applications. The fellowship is available for a year (April 1999 - March 2000) in the first instance. The fellowship involves extensive contact with UK and international research institutions and close liaison with other operational divisions within BT. This position is ideal for a young and enterprising researcher, or indeed for an academic who wants to realise his/her ideas in industry. The department has extensive collaborations with leading UK, European and American universities. BT Laboratories (BTL), at Martlesham Heath in the east of England, is acknowledged as one of the world leading telecommunications R&D centres in terms of both size and excellence. JOB DESCRIPTION: Play a major part in the research, design and development of biologically motivated (or nature-inspired) computing techniques, paradigms, applications, novel computing *thinking*, and develop proof-of-concept demonstrators. Play a major role in identifying new applications of such ideas. Candidates with good grounding of A-Life and evolutionary computing type techniques are especially welcome to apply. SKILLS REQUIRED: PhD, MSc. or equivalent research experience in an area related to biologically motivated (nature inspired) computing. However, candidates who want to draw from other areas in order to bring **new and radical thinking** to computing are also especially welcome to apply. Good innovation skills and software programming experience including Java, C++ and C, under PC and UNIX environments. High motivation and good interpersonal, teamworking, writing and communication skills. CONTACT INFORMATION: If you meet the job description and skills required and you are interested, please email CVs (postscript or plain ASCII text ONLY) and covering letters to the following address: hyacinth@info.bt.co.uk Alternatively, send snail mail to Dr. Hyacinth S. Nwana Admin 2, PP5, BT Laboratories, Martlesham Heath, Ipswich IP5 3RE England. Tel: +44 1473 605457 Fax: +44 1473 647410 ------------------------------ Date: Mon, 14 Dec 1998 09:49:06 -0500 (EST) From: Bill Punch Subject: Reminder, CEC99 Deadline Jan 15, 1999 CALL FOR PAPERS, 1999 Congress on Evolutionary Computation, July 6-9, Renissance Hotel, Washington D.C. The 1999 Congress on Evolutionary Computation will be the first conference to bring together the entire evolutionary computation field in all of its diversity in a single event. CEC99 is a joint meeting of the IEEE International Conference on Evolutionary Computation (ICEC), the Conference on Evolutionary Programming (EP), and Genetic Algorithms in Engineering Systems: Innovations and Applications (GALESIA), three of the broadest and most inclusive conferences in the field today. This event is sponsored by the IEEE Neural Networks Council, the Evolutionary Programming Society, and the Institution of Electrical Engineers (IEE). CEC99 will provide an inclusive forum for the presentation of the most recent progress in all aspects of this burgeoning field while fostering communication and progress towards a better understanding of the issues facing evolutionary computation in all forms and applications. Appropriate paper topics include, but are not limited to, theory, application, empirical analysis, and philosophy concerning all manner of evolutionary computation including evolution strategies, evolutionary programming, genetic algorithms, genetic programming, classifier systems, artificial life, DNA computing, evolvable hardware, evolutionary robotics, and any hybridized search, optimization, or machine learning techniques drawing on computational models of evolution. Additional topics of interest include evolutionary optimization, evolutionary design, evolution of neural networks, co-evolutionary learning systems, co-evolution of coordinated action and other applications of evolutionary computation to intelligent system creation. Papers investigating issues common to all evolutionary computations are especially encouraged. All submitted manuscripts must be original, unpublished work that is not currently under consideration for any other conference or journal. The submission deadline is January 15, 1999. Questions, concerns, and inquiries can be sent to the conference email at CEC99@natural-selection.com. For additional information and future conference updates see the conference web pages at http://garage.cps.msu.edu/cec99. ------------------------------ Date: Mon, 14 Dec 1998 18:34:43 -0800 (PST) From: Jason Lohn To: GA-List@AIC.NRL.Navy.Mil Subject: CFP: The First NASA/DOD Workshop on Evolvable Hardware First Call for Papers The First NASA/DOD Workshop on Evolvable Hardware July 19-21, 1999 Jet Propulsion Laboratory Pasadena, California, USA Sponsored by: National Aeronautics and Space Administration (NASA) Defense Advanced Research Projects Agency (DARPA) Ballistic Missile Defense Organization (BMDO) Co-hosted by: JPL Center for Integrated Space Microsystems (CISM) JPL Center for Space Microelectronics Technology (CSMT) The First NASA/DOD Workshop on Evolvable Hardware (EH'99) will be held at the Jet Propulsion Laboratory in Pasadena, California. The purpose of this workshop is to bring together leading researchers from the evolvable hardware community, representatives of the programmable/reconfigurable hardware community, technology developers, and end-users from the aerospace community. The emerging field of Evolvable Hardware is expected to have major impact on deployable systems for space missions and defense applications that need to survive and perform at optimal functionality during long duration in unknown, harsh and/or changing environments. Examples of such applications include outer solar system exploration, missions to comets and planets with severe environmental conditions, long lasting space-borne surveillance platforms, defensive counter-measures, long-term nuclear waste and other hazardous environment monitoring and control. Evolvable hardware is also expected to greatly enrich the area of commercial applications in which adaptive information processing is needed; such applications range from human-oriented hardware interfaces and internet adaptive hardware to automotive applications. The purpose of the workshop is to provide a forum for discussion on the potential role of evolvable hardware in real-world applications, in particular those related to space. The Workshop attendees will have the opportunity to discuss the fundamental issues and state-of-the art of evolvable hardware technology, plans for development of future devices and hardware systems suitable for evolution, and needs related to space applications. The outcome of this meeting is expected to be a technology development roadmap that would lead to deployable evolvable hardware. Topics to be covered include, but are not limited to: * Evolutionary hardware design (including design of mechanical systems, electronic circuits synthesis) * Co-evolution of hybrid systems (including hybrids of wetware, chemical, mechanical, and electronic components, etc.) * Evolving hardware systems * Intrinsic, and on-line evolution * Hardware/software co-evolution * Self-repairing hardware * Embryonic hardware * Morphogenesis * Tools supporting evolvable hardware * Novel devices and hardware platforms suitable for evolution * Adaptive hardware, adaptive computing * Adaptive flight hardware * Real-world applications of EHW IMPORTANT DATES: Submission deadline: February 24, 1999 Author notification: April 2, 1999 Camera ready manuscript deadline: May 1, 1999 Workshop: July 19-21, 1999 For further information please check the workshop web site or contact: Adrian Stoica Jet Propulsion Laboratory, MS 303-300 4800 Oak Grove Drive Pasadena, CA 91109, USA adrian.stoica@jpl.nasa.gov Tel: +1 (818) 354 2190 Fax: +1 (818) 393 4272 [MAP: The URL for the workshop Web site is http://cism.jpl.nasa.gov/events/nasa_eh ] ------------------------------ Date: Tue, 15 Dec 1998 14:52:56 CET From: "Pavel Osmera,KINF,/3332" Subject: CFP: MENDEL'99 TECHNICAL UNIVERSITY OF BRNO FACULTY OF MECHANICAL ENGINEERING Institute of Automation and Computer Science DAAAM - International Vienna Foundation Advanced Information Technology GENOPS, Ltd. First Announcement - call for papers MENDEL '99 5th International Mendel Conference on Soft Computing 100th Anniversary of the Technical University of Brno Evolutionary Computation, Genetic Programming, Fuzzy Logic, Neural Networks, Rough Sets, Fractals. June 9 - 12, 1999 BRNO, CZECH REPUBLIC In 1865 Gregor Johann Mendel, an Augustinian priest in a Brno monastery, described to the Brno Natural Science Society the transfer of determinants in pea plants. Sadly, the fundamental importance of Mendel's finding were not understood by the Society. Until 1900 no one realized that Mendel had discovered the Law of Heredity. Brno, the workplace of the father of genetics and the conference organizers, is very pleased to offer a conference platform for modern engineering using the principles of heredity. The MENDEL '99 Conference organisers wish to create a base for a theoretical and practical exchange of knowledge of evolution theories in Central and Eastern Europe. Theoretical papers that relate to the conference topic are invited, as are any practical results and knowledge from the field of evolution strategies in mathematics, research, education, etc. SCOPE The scope of the Conference includes, but is not limited to: Innovation and Theory - genetic operators and representations - hybrid and distributed algorithms - genetic algorithms for neural networks - parallel genetic algorithms - genetic programming - evolutionary programming - mathematical techniques and analysis - biological aspects of GAs - fuzzy logic - neural networks - rough sets - fraktals Applications - optimization problems - machine learning - scheduling algorithms - signal processing - robotics - vision system/applications - process industry - control systems - manufacturing - system identification - decision-making - economics - biomedical The Conference invites researchers in the field of Engineering Systems or related fields in Mathematics, Physics, Computer Science, etc. Workers in other areas such as Biology, Psychology and Medicine are also welcome. DEADLINES March 15, 1999 Submission of paper: 3 hard copies & soft copy (postscript file via 3,5'' diskette or e-mail) April 15, 1999 Notification of acceptance to authors April 30, 1999 Preliminary program May 15, 1999 Payments Doc.Ing.Pavel Osmera,CSc. Technical University Brno Fakulty of Mechanical Engineering Institute of Information Technology Technicka 2 616 69 BRNO Czech Republic phone: +420-5-41143334 fax: +420-5-41211994 e-mail: osmera@kinf.fme.vutbr.cz [MAP: For more information see the conference Web site at http://www.fme.vutbr.cz/html/UAI/confs/men99.html ] ------------------------------ Date: Wed, 16 Dec 1998 13:10:53 +0100 From: Moshe Sipper Subject: CFP: Evolutionary Computation in Medicine SECOND CALL FOR SUBMISSIONS Special Issue of the Journal "Artificial Intelligence in Medicine" (Published by Elsevier) Theme: EVOLUTIONARY COMPUTATION IN MEDICINE Guest-Editors: Eytan Ruppin, James A. Reggia, and Moshe Sipper Tel-Aviv U., Univ. Maryland, EPFL -- Lausanne BACKGROUND The idea of applying the biological principle of natural evolution to artificial systems, introduced more than four decades ago, has seen impressive growth in the past few years. Usually grouped under the term "evolutionary algorithms" or "evolutionary computation," we find the domains of genetic algorithms, evolution strategies, evolutionary programming, and genetic programming. Central to all these different methodologies is the idea of solving problems by evolving an initially random population of possible solutions, through the application of "genetic" operators, such that in time increasingly "fit" (i.e., better) solutions emerge. Evolutionary algorithms have been successfully applied to numerous problems from different domains, including optimization, automatic programming, machine learning, and economics. As evolutionary computation studies have advanced during the last several years, there has been an increasing interest in adopting them to investigate a wide range of domains in medicine, ranging from the modeling of the immune system to epidemiological studies of disease spread, population genetics, and more generally, as optimization and classification tools for improved diagnosis and decision-making systems in medicine. OBJECTIVES OF THE SPECIAL ISSUE The objective of this special issue on evolutionary computation in medicine is to report on the recent studies in this field. The main goal is to increase the awareness of the AI medical community to this research, currently primarily carried out by members of the evolutionary computation community. By bringing together a series of evolutionary computation papers we strive to produce a contemporary overview of the kinds of problems and solutions that this growing research field has generated, and to point to promising future avenues of research. The papers are expected to cover one or more of the following three primary themes: -- Using evolutionary algorithms to study and model basic questions in medical research. -- Applications of evolutionary computation algorithms to medical diagnosis and management, with emphasis on a systematic comparison of the latter with other existing methods. -- Methodological issues involved in applying evolutionary computation to study problems in medicine, including obtaining sufficient data and normalizing it, methods for reducing the search space dimension, choices between different evolutionary computation techniques, and testing and validating the results. TIMELINE All submitted manuscripts will be subject to a rigorous review process. The special issue will include five (5) papers of 15-20 pages each, plus an editorial. A double issue will be considered in the case of sufficient papers worthy of publication. Manuscripts should be prepared in accordance with the journal "submission guidelines," which are available on request, and may also be retrieved from http://www.elsevier.nl/locate/aimed. February 15, 1999 Submission of tentative title and brief abstract to declare intention to submit paper. This should be done electronically, to: ruppin@math.tau.ac.il. March 15, 1999 Receipt of full papers. Three copies of a manuscript should be sent to: Eytan Ruppin Department of Computer Science School of Mathematics Tel-Aviv University Tel-Aviv, Israel, 69978. August 1, 1999 Notification of acceptance October 1, 1999 Receipt of final version of manuscripts Mid 2000 Publication of AIM special issue ------------------------------ Date: Mon, 21 Dec 1998 11:25:42 -0500 (EST) From: aswu@AIC.NRL.Navy.Mil Subject: GECCO-99 Workshops GECCO-99 Bird-of-a-feather Workshop Summaries The GECCO-99 Program Committee is pleased to announce that the following Bird-of-a-feather workshops to be held during the 1999 Genetic and Evolutionary Computation Conference (GECCO-99). For information regarding participating or presenting at a particular workshop, please see the workshops homepage at http://www-illigal.ge.uiuc.edu/gecco/workshops.html. For general inquiries regarding workshops, please contact Annie Wu at aswu@aic.nrl.navy.mil. Joint AAAI-99 and GECCO-99 Workshop (to be held on July 17 or 18, 1999): == Data mining with evolutionary algorithms: Research directions == Alex A. Freitas There has been a growing interest in data mining in several AI-related areas, including evolutionary algorithms. Hence, it seems that it is the right time for the communities of data mining and evolutionary algorithms to meet and exchange ideas. The general goal of the workshop will be to discuss promising and necessary research directions in data mining with evolutionary algorithms. GECCO-99 Workshops (to be held on July 13, 1999): == Evolutionary algorithms for dynamic optimization problems == Juergen Branke and Thomas Baeck Many real-world optimization problems are eventually dynamic. New jobs are to be added to the schedule, the quality of the raw material may be changing, new orders have to be included into the vehicle routing problem etc. In such cases, when the problem changes over the course of the optimization, the purpose of the optimization algorithm changes from finding an optimal solution to being able to continuously track the movement of the optimum through time. Since natural evolution is a process of continuous adaptation, it seems straightforward to consider evolutionary algorithms as appropriate candidates for dynamic optimization problems. And indeed, the interest in evolutionary algorithms for dynamic optimization problems is growing and a number of authors have proposed an even greater number of new approaches. However the field seems to lack a general understanding as to suitable benchmark problems, fair comparisons, or measurement of algorithm quality. == Evolutionary Computation and Parallel Processing == Erick Cantu-Paz and Bill Punch Evolutionary Computation researchers have long had an interest in parallel processing, due to the ease with which many EC algorithms can be implemented in a parallel fashion. Furthermore, many real-world applications of EC require some parallel processing in order to make practical progress. This workshop invites discussion on general issues of parallel processing in the context of EC, including (but not necessarily limited to): - theory applied to EC parallel processing (population sizing, speedup, etc.) - innovative EC parallel processing (unique topologies, fitness averaging, etc.) - controlled experimental studies - practical examples of EC parallel processing - hardware/software considerations (Beowulf processing, distributed parallel processing, etc.) == Evolutionary computation visualization == Trevor Collins Software visualization is an area of computer science devoted to supporting people's understanding and effective use of computer software. Within Evolutionary Computation, visualization is increasingly being used as a means for supporting people's understanding of their algorithm's behavior. This workshop offers a timely opportunity for people interested in the possibilities of visualization to see the current state of the art, discuss the contribution that this work makes, and influence the future work done in this area. == Multi-criterion optimization using evolutionary methods == Kalyanmoy Deb For last five years or so, the research on multi-criterion optimization using evolutionary algorithms (EAs) has received a growing attention. This is rightly so, because population-based EAs allow a unique way to find multiple Pareto-optimal solutions in multi-criterion search and optimization problems. To date, there exists successful EA implementations and a number of engineering applications in this area. In this workshop, we intend to present the research results that have been achieved already and discuss how and what topics should be emphasized for future research. 1. Theoretical development of multi-objective EAs 2. Implementations of multi-objective EAs 3. Comparison of different multi-objective EAs 4. Interesting multi-objective EA applications 5. Future directions for research == Advanced grammar techniques within genetic programming and evolutionary computation == Talib Hussain The basic genetic programming paradigm involves the use of genetic representations and genetic manipulations based upon simple context-free grammars and Koza's closure property. A number of researchers have recently examined variations to these aspects of GP. In particular, some researchers have relaxed the closure property (e.g., Strongly Typed Genetic Programming) while others have considered more complex grammar types (e.g., logic grammars and attribute grammars). As well, in EC in general, a variety of grammar techniques have been used (e.g., Lindenmayer systems). Is vanilla GP sufficient for the evolution of solutions to all complex problems? Obviously not. It is therefore important for us to consider variations upon GP which may improve its applicability to hard problems. Incorporating increased complexity into the genetic representations and manipulations is one obvious course of exploration. The various advanced grammar techniques being used for such exploration face common issues and are drawing similar conclusions. Rather than continuing to tout each technique independently (e.g., STGP, cellular encoding, etc), the EC community should try to discover what these techniques have in common and where they are leading us. This workshop aims to present a cross- section of current research and promote a discussion of fundamental issues concerning grammar design in evolutionary algorithms. == Coevolutionary algorithms and coevolving agents == Colin G. Johnson, Bjorn Olsson, and Steve Romaniuk In solving complex tasks using evolutionary methods there are often many conflicting requirements, and there are many complexities in breaking down a complex problem into effective subproblems. It has been proposed that such complexities can be handled by coevolutionary interactions, such as cooperation, competition and host-parasite or predator-prey interaction. This workshop will consider ways in which these coevolutionary processes can be applied to improving the performance of evolutionary lgorithms, both in improving the performance of algorithms in existing roblem domains and using the techniques to solve problems which are not menable to conventional evolutionary computing techniques. Combining volutionary computing ideas with the problem decomposition and istributed solution techniques which lie at the heart of innovations uch as agent technology provide a powerful paradigm for problem olving in many domains. These techniques provide a cyber-diversity of roblem-solving methods which echo the bio-diversity found in nature. == Evolutionary computation economics == M. A. Kaboudan Evolutionary Computational Economics is a workshop to present theoretical developments in and applications of evolutionary computations in business and economic decision-making. Theoretical developments delineate analyzing statistical properties of evolutionary & genetic computations. Applications foster the use of evolutionary computations in developing forecasting models in financial, economic, and nonlinear systems. Anyone interested in presenting a paper involving theoretical developments in and applications of evolutionary & genetic computations in business and economic decision-making should contact the workshop organizer. == 2nd International workshop on learning classifier systems == Pier Luca Lanzi, Wolfgang Stolzmann, and Stewart W. Wilson The goal of this workshop is to discuss the recent developments in learning classifier systems (LCSs) research and the expected trends of the field. LCSs were introduced by John Holland (1978) as a method of learning by interacting with an environment, based on a biological metaphor: learning is viewed as a process of ongoing adaptation of an agent to an initially unknown environment. For a long time the LCS paradigm has been considered limited to the evolutionary computation community and their applications were limited to well-defined fields, e.g. robotics. The recent developments in the field of reinforcement learning have brought new attention to the LCS paradigm, which has been shown to be an interesting alternative to traditional reinforcement learning techniques. Furthermore, LCSs can be competitive in more general contexts like: autonomous agents, classification, trading agents, and personal assistants. Because of these new developments it is important to bring together people from this field for getting an overview of the latest results and most promising research directions. == Computational models in theoretical biology == Carlo C. Maley "Mathematical and computational approaches to biological questions, a marginal activity a short time ago, are now recognized as providing some of the most powerful tools in learning about nature; such approaches guide empirical work and provide a framework for synthesis and analysis." (Levin et al. 1997) This workshop will be devoted primarily to configuration/individual-based/agent-based models and their connections to both analytical theory and experiment. The workshop will be focused a combination of results along with methodological issues and approaches to the problem of contributing to biology through theory. Methodological issues include: Determining what to put in and what to leave out of a model, representation and implementation of biological systems, testing the accuracy of a model, and applying the results to the real world. We anticipate contributions in, but not limited to, evolutionary theory, ecological theory, immunology, paleobiology, and epidemiology. == Evolvability == Paul Marrow, Mark Shackleton, Jose-Luis Fernandez, and Tom Ray Evolvability is a central issue in evolutionary computation, but remains little understood. It has attracted some interest among workers in evolutionary computation (examples are Altenberg 1994; Wagner & Altenberg 1996) and biology (Dawkins 1989; Kirschner & Gerhart 1998). Much remains to be done, both in understanding the nature of evolvability and working out how to enhance evolvability for the benefit of evolutionary algorithm performance. This workshop will focus on understanding evolvability, how to quantify its characteristics, and how to exploit evolvability to improve algorithm performance. == Foundations of genetic programming == Una-May O'Reilly, Thomas Haynes, Riccardo Poli, Bill Langdon, Justinian Rosca Producing useful theoretical results in genetic programming has been very difficult, although the situation is improving now. In the workshop we want: - to identify the reasons why progress is so difficult. That is, what makes GP theory difficult to obtain? - to brainstorm on what we can do to remove these obstacles, and - to specifically map out the most promising directions in which the community should start moving == Evolution of sensors in nature, hardware, and simulation == Daniel Polani, Thomas Uthmann, and Kerstin Dautenhahn In natural evolution one finds impressive examples for the principle of exploiting new sensory channels and making use of the implicit information they encode. Olfactory, tactile, auditive and visual, but also e.g. electric and even magnetic senses have emerged in a vast multitude of variants, often utilizing organs not originally "intended" for the purpose they serve at present. Motivated by these observations, the topic of sensor evolution is becoming a very modern and promising direction of research situated between biology, robotics and Artificial Life. Research in this direction strives at: 1. insights into how biological systems evolve strategies to access new information channels 2. new concepts for design of sensors for flexible and adaptive autonomous agents, an important issue in evolutionary robotics 3. an understanding of the relationship between the information available to an agent and the way it is processed, which is of particular interest for Artificial Life research. == Evolutionary telecommunications: Past, present, and future == Mark C. Sinclair, David Corne, and George D. Smith Telecommunications is a vital and growing area, important not only in its own right, but also for the service it provides to other areas of human endeavour. However, telecommunications, supported by an ever-changing set of technologies and providing an ever-expanding set of services, presents a challenging range of difficult design and optimisation problems. In recent years, there has been increasing interest in the application of evolutionary computation (EC) to these problems, including network design, call routing, signal processing, frequency assignment, wavelength allocation, capacity planning, admission control, network management, and many others. Recognising the potential of evolutionary telecommunications, as this synergy has been styled, the workshop will focus on EC for telecommunications applications, particularly those involving areas unique to telecommunications, such as network design. The two main aims will be to establish the current state of the art in the field, as well as to discuss useful directions for future research in this important area. == Getting our bearings in DNA computing == David Harlan Wood This workshop will attempt to clarify the outstanding unresolved issues in DNA computing. Issues and opinions are solicited. A brief and incomplete list of concerns is given below. The organizer would very much like to to have other issues raised, and suggestions for the format of the workshop. 1. What are our accomplishments in DNA computing to date? 2. What is a problem for which DNA based computing is the preferred solution method? 3. Can laboratory techniques be found or modified to address the need for low error rates? 4. What are the physical limits on using DNA laboratory techniques on large quantities of DNA? 5. What aspects of DNA computing are most analogous to conventional computation? 6. Are new, stochastic, models of computation needed? 7. Can one encode information into strands of DNA using A-T and C-G paring in such a way the strands pair up (hybridize) only where they are supposed to? 8. What are the immediate problems in DNA computing that need to be addressed? For information on attending, participating, or presenting at any of these workshops, please see http://www-illigal.ge.uiuc.edu/gecco/workshops.html. ------------------------------ End of Genetic Algorithms Digest ******************************