Genetic Programming and Evolvable Machines

Special Issue on

Developmental Systems

 

 

 

Special Issue Guest Editors

 

Gregory Hornby

University of California, Santa Cruz

at NASA Ames Research Center

 

Christian Jacob

Dept. of Computer Science and

Dept. of Biochemistry &

Molecular Biology

University of Calgary

 

Sanjeev Kumar

Sibley School of Mechanical & Aerospace Engineering,

Cornell University

 

 

 

 

-- Special Issue Schedule --

Submission deadline: March 31, 2006

Notification of acceptance: September 30, 2006

Final manuscript: December 31, 2006

 

 

   

Synopsis

Evolutionary algorithms have been applied to an ever increasing variety of design domains, for which they have achieved human competitive results on small design problems. In order to improve the applicability of such systems, fundamental research must be undertaken to discover how to construct increasingly more sophisticated designs.

 

To this end, human engineering has produced sophisticated devices and objects (such as aircraft with over a million parts, computer software, microprocessors, etc.) suggesting that we can improve the scalability of automated design systems by using principles of engineering, and thereby begin to automate the design process. However, these systems also show the challenges related to manual design and construction: scalability, adaptability, and modularization.

 

In nature, the processes of biological development have been pivotal in nature's ability to construct adaptable, modularized, self-maintaining, and self-repairing systems of incredible complexity. Heralded as a brilliant triumph of evolution, the development of multicellular organisms from a single cell provides a plentiful and rich source of knowledge and inspiration for the construction of developmental systems both for modeling biology and for building evolutionary design systems for computer-automated design.

 

It is anticipated that insights gained into mechanisms of construction using models of biological cells and multicellular development will play an important role in not only helping us gain a better understanding of the underlying biological processes, but also in helping us learn more about the general design principles utilized in development and evolution. The ultimate goal would then be to apply these to practical design problems in engineering.

 

Fundamental to the successful applicability of such systems is the need for targeted research toward identification and abstraction of key constructional aspects of natural developmental systems, their interaction with the environment, and the ability to evolve increasingly more sophisticated designs. Naturally, evolutionary algorithms will play a key role in 'developmental engineering' -- both for constructing modular designs and for their adaptive fine-tuning. Regardless of the model of development or generative representation chosen -- cellular automata, genetic regulatory networks, L-systems, etc -- we must understand exactly what gives such systems their computational power and exactly how they affect evolvability.

 

 

Topics of Interest Include:

 

·        Applications, especially real-world applications of developmental principles.

·        Automatic abstraction and encapsulation of modules.

·        Benchmark design problems.

·        Computational developmental systems and artificial ontogenies.

·        Efficient and adaptive genotype-phenotype mappings.

·        Evolvability.

·        Generative representations.

·        Genetic regulatory networks.

·        Models of Pattern Formation, Morphogenesis, Differentiation, Cell Signaling and Signal Transduction.

·        Modularity, segmentation and compartmentalization

·        Open-ended design.

·        Properties of Evolutionary Design Systems.

·        Relationship between evolution and development.

·        Reviews and comparisons of Evolutionary Design Systems.

·        Role of environmental interaction and simulated physics/chemistry.

·        Scalability.

·        Self-repair.

·        Theory showing the advantages/disadvantages of developmental principles or generative representations.

 

 

Submission Procedure

 

The submission/publication schedule is listed at the top of this page. All electronic submissions must be sent to Greg Hornby at: hornby@email.arc.nasa.gov

 

Manuscripts should conform to the standard format of the Genetic Programming and Evolvable Machine journal as indicated in the Information for Authors. All submissions will be peer reviewed subject to the standards of the journal. Manuscripts based on previously published conference papers must be extended substantially. Electronic submissions must be in PDF format.

 

All enquiries on this special issue should be sent to Greg Hornby at: hornby@email.arc.nasa.gov

Prospective authors are also invited to send an email to Greg Hornby indicating their interest in submitting a paper and the specific topics addressed.

 

 

 Journal Website

 

The website for the journal Genetic Programming and Evolvable Machines is at:

http://www.springeronline.com/sgw/cda/frontpage/0,11855,4-40109-70-35574852-0,00.html

 

 

Related Links

 

·        Scalable, Evolvable, Emergent Design and Developmental Systems (SEEDS), GECCO '05
  http://www.cs.ucl.ac.uk/staff/S.Kumar/seeds.htm

·        Self-Organization in Nature-Inspired Computation (SONIC). New discussion mailing group for self-organization in nature-inspired computation and related research topics. Subscription information here.

·        Self-Organization and Development in Artificial and Natural Systems (SODANS), ALIFE 9 2004 http://www.cs.ucl.ac.uk/staff/S.Kumar/sodans.htm

·        Regeneration and Learning in Developmental Systems (WORLDS), GECCO '04
  http://www.elec.york.ac.uk/intsys/users/jfm7/worlds.htm

·        Modularity, Regularity, and Hierarchy in Evolutionary Computation, GECCO '04
  http://www.mae.cornell.edu/lipson/gecco_modularity.htm

·        Self-Organization on Representations for Genetic and Evolutionary Algorithms, GECCO '04
  http://ivan.research.ucf.edu/SOEA.htm

·        Computational Synthesis: From Basic Building Blocks to High Level Functionality, AAAI Spring Symposium '03
  http://www.mae.cornell.edu/ccsl/conferences/AAAI_2003_CS/

 

 

 

 

 

Pine pollen image courtesy of Paul Schulte