Published quarterly by: MIT Press Journals, 55 Hayward Street, Cambridge, MA 02142-1399, USA. Tel: (617) 253-2889, Fax: (617) 258-6779, <email@example.com>
Along with the explosive growth of the computing industry has come the need to design systems capable of functioning in complex, changing ENVIRONMENTs. Considerable effort is underway to explore alternative approaches to designing more robust computer systems capable of learning from and adapting to the environment in which they operate.
One broad class of such techniques takes its inspiration from natural systems with particular emphasis on evolutionary models of computation such as GAs, ESs. CFS, and EP. Until now, information on these techniques has been widely spread over numerous disciplines, conferences, and journals. [eds note: The editorial board reads like a who-is-who in EC.] For paper e-mail submission, use one of the following addresses:
Please note, that submissions should be sent to one of the sub-editors. Grefenstette and Kitano accept LaTeX or PostScript submissions.
Journal of Biological and Information Processing Sciences, Elsevier Science Publishers, P.O. Box 1527, 1000 BM Amsterdam, The Netherlands.
BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
Topics: Molecular EVOLUTION: Self-organizing and self-replicating systems, Origin and evolution of the genetic mechanism; Biological Information Processing: Molecular recognition, Cellular control, Neuromuscular computing, Biological adaptability, Molecular computing technologies; EVOLUTIONARY SYSTEMS: Stochastic EVOLUTIONARY ALGORITHMs, Evolutionary OPTIMIZATION, SIMULATION of genetic and ecological systems, Applications (neural nets, machine learning, robotics))
The IEEE Transactions on Evolutionary Computation will publish archival journal quality original papers in EVOLUTIONARY COMPUTATION and related areas, with particular emphasis on the practical application of the techniques to solving real problems in industry, medicine, and other disciplines. Specific techniques include but are not limited to EVOLUTION STRATEGIEs, EVOLUTIONARY PROGRAMMING, GENETIC ALGORITHMs, and associated methods of GENETIC PROGRAMMING and CLASSIFIER SYSTEMs. Papers emphasizing mathematical results should ideally seek to put these results in the context of algorithm design, however purely theoretical papers will be considered. Other papers in the areas of cultural algorithms, ARTIFICIAL LIFE, molecular computing, evolvable hardware, and the use of simulated evolution to gain a better understanding of naturally evolved systems are also encouraged.
Papers must conform to IEEE standard submission guidelines which are available in IEEE transactions (for example, see the IEEE Transactions on Neural Networks or the IEEE Transactions on Fuzzy Systems). Those wanting to receive an author's information booklet from the IEEE can request this at <firstname.lastname@example.org>.
Six (6) hard copies of the manuscript should be sent to: David B. Fogel, Editor-in-Chief, IEEE Transactions on Evolutionary Computation, c/o Natural Selection, Inc., 3333 N. Torrey Pines Ct., Suite 200, La Jolla, CA 92037, USA.
The editor-in-chief will be pleased to comment on the suitability of other submissions at the request of the authors. Further questions can be directed to <email@example.com>. The transactions will appear quarterly.
Published by: Complex Systems Publications, Inc., P.O. Box 6149, Champaign, IL 61821-8149, USA.
Complex Systems devotes to the rapid publication of research on the science, mathematics, and engineering of systems with simple components but complex overall behavior. Try finger(1) on <firstname.lastname@example.org> for additional info.
Published by: Kluwer Academic Publishers, P.O. Box 358, Accord Station, Hingham, MA 02018-0358 USA.
Machine Learning is an international forum for research on computational approaches to learning. The journal publishes articles reporting substantive research results on a wide range of learning methods applied to a variety of task domains. The ideal paper will make a theoretical contribution supported by a computer implementation.
The journal has published many key papers in learning theory, reinforcement learning, and decision tree methods. The journal regularly publishes special issues devoted to GAs and CFS as well.
Published quarterly by: MIT Press Journals, details above.
Broadly, behavior is adaptive if it deals successfully with changes circumstances. For example, when surprised, a hungry --but environmentally informed-- mouse may dart for cover rather than another piece of cheese. Similarly, a tripped-up ROBOT [eds note: not necessarily built by Sirius Cybernetics Corp.] could get back on its feet and accomplish a moonrock-finding mission if it had learned to cope with unanticipated lunar potholes.
Adaptive Behavior thus takes an approach complementary to traditional AI. Now basic abilities that allow animals to survive, or robots to perform their mission in unpredictable ENVIRONMENTs, will be studied in preference to more elaborate and human-specific abilities.
The journal also aims to investigate which new insights into intelligence and cognition can be achieved by explicitly taking into account the environment feedback --mediated by behavior-- that an animal or a robot receives, instead of studying components of intelligence in isolation.
Topics: INDIVIDUAL and Collective Behavior. Neural Correlates of Behavior. Perception and Motor Control. Motivation and Emotion. Action SELECTION and Behavioral Sequences. Internal World Models. Ontogeny, Learning, and EVOLUTION. Characterization of environments.
Published quarterly by: MIT Press Journals, details above.
Artificial Life is intended to be the primary forum for the dissemination of scientific and engineering research in the field of ARTIFICIAL LIFE. It will report on synthetic biological work being carried out in any and all media, from the familiar "wetware" of organic chemistry, through the inorganic "hardware" of mobile robots, all the way to the virtual "software" residing inside computers.
Research topics ranging from the fabrication of self-replicating molecules to the study of evolving POPULATIONs of computer programs will be included.
There will also be occasional issues devoted to special topics, such as L-Systems, GENETIC ALGORITHMs, in-vitro evolution of molecules, artificial cells, computer viruses, and many social and philosophical issues arising from the attempt to synthesize life artificially.
[eds note: The editorial board reads like a who-is-who in ALIFE]
Published quarterly by: Springer-Verlag New York, Inc., Service Center Secaucus, 44 Hartz Way, Secaucus, NJ 07094, USA. Tel: (201) 348-4033, Fax: (201) 348-4505.
Evolutionary Economics aims to provide an international forum for a new approach to economics. Following the tradition of Joseph A. Schlumpeter, it is designed to focus on original research with an evolutionary conception of the economy. The journal will publish articles with strong emphasis on dynamics, changing structures (including technologies, institutions, beliefs, imitation, etc.). It favors interdisciplinary analysis and is devoted to theoretical, methodological and applied work.
Research areas include: industrial dynamics; multi-sectoral and cross-country studies of productivity; innovations and new technologies; dynamic competition and structural change in a national and international context; causes and effects of technological, political and social changes; cyclic processes in economic evolution; the role of governments in a dynamic world; modeling complex dynamic economic systems; application of concepts, such as self-organization, bifurcation, and chaos theory to economics; evolutionary games.
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Hitch Hiker's Guide to Evolutionary Computation, Issue 9.1, released 12 April 2001
Copyright © 1993-2001 by J. Heitkötter and D. Beasley, all rights reserved.