[alife] CFP: Special Issue on Artificial Chemistry

[Peter Dittrich]

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             Call for Papers on Artificial Chemistry

                 Special Issue of Artificial Life
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Submission Deadline:  October 2nd, 2006

Guest Editors: Hideaki Suzuki, Peter Dittrich
Editor-in-Chief: Mark Bedau


"Artificial chemistry" (AChem) provides a promising research approach
to understand and synthesize life.  By preparing an abstract
environment analogous to prebiotic conditions, to a protocell
experiment, or to a living cell, AChem provides a powerful workbench
to simulate the components of living systems. Furthermore, we can not
only study mechanisms governing the emergence of life and the early
stages of biological evolution, but also get design clues for novel
computational systems or novel self-organizing nano-scale devices
that have desirable features in common with living systems.

AChem is defined as a bunch of studies that use an abstract
model of chemical molecules and their reactions.
By manipulating artificial molecules, atoms, or
moelcular/atomic clusters individually, using a discrete or
continuous information space, AChem provides a powerful capability
for emulating molecular interactions and the emergence of other 
chemical phenomena on an abstract level. 
This makes AChem different from traditional computational
chemistry models that focus too much on an acurate modeling of real
physico-chemistry and, as a consequence, suffer from the problem of
computational cost.

Recently, AChem has been extended into a broad domain, which includes
investigations of theories, models, algorithms, experimental systems,
and applications. Domains tackled by artificial chemistries include:
the molecular basis for the origin of life [Segre et al. 1998],
complex metabolic or reaction networks [Suzuki 2004], spontaneous
pattern formation [Turing 1952], the formation of social order
[Szuba/Stras 1997], or concurrent information processing systems
[Banatre 1996, Berry/Boudol 1992].

On the other hand, artificial chemistries are used in technical
applications, such as control [Ziegler/Banzhaf 2001] or
optimization [Kanada 1995]. Examples for promising application areas
are: the control of multi-component artifacts, control of highly
distributed ad-hoc networks, artificial morphogenesis, the exploration
of the functional building blocks of minimal programmable cells
(cf. PACE-project), or the synthesis or crystallization of new
(in)organic compounds.

Implementation methods for artificial chemistries are ranging
from differential equation models [Eigen/Schuster 1977, Turing
1952, Jain/Krishna 2001] to explicit stochastic systems involving
molecules possessing a structures that implies their function
[Fontana/Buss 1994]. Furthermore, artificial chemistries are not
restricted to computer simulations, but can also been instantiated in
physical systems, e.g., the self-assembling triangles by Hosokawa et
al. [1994] or the rotating magnetic discs by Grzybowski et al. [2000].

We aim to collect papers on recent advances in AChem studies, for a
special issue showcasing the state of the art of this field.
Important open problems approached by artificial chemistry research 
include:

* How to create an artificial chemistry with a given desired property?
This question is closely related to how to program a chemical system.

* How to construct an abstract/theoretical model for self-organization?
Or, how to predict and explain the macroscopic behavior of an artificial
chemistry?  These questions aim at a theory of artificial chemistries
or theory of chemical emergence, which is not limited to artificial
reaction systems.

* How to validate artificial chemistries using real world data?
If artificial chemistries should explain aspects of life and its origin,
they should be quantitatively or at least qualitatively justified by
real chemistry.

* How to create an artificial chemistry that autonomously evolves and
creates an increasing amount of complexity, e.g., that produces
spontaneously several levels of hierarchies?
(related to study of the origin of life)

* How can an artificial chemistry be used to explain aspects of biological
life?
(related to biology and organic chemistry)

* How can an artificial chemistry be employed as an internal tool in
technical systems?
(cf. computational intelligence, organic computing, autonomous systems)

* What would it mean to program (artificial) chemistries and how
would we proceed in doing it?
(related to unconventional computing)

* How to make a minimal artificial system (computational or physical)
that captures the main principles of a living cell?

* How to make an artificial cell? Which includes the questions:
How to make artificial chemistries for an artificial cell?
How to make an artificial chemistry where cells emerge, grow, replicate, 
and
evolve?


List of referees (in alphabetical order)

Wolfgang Banzhaf (University of New Foundland, Canada)
Peter J Bentley (University College London, UK)
Dominique Chu (University of Birmingham, UK)
Peter Dittrich (Friedrich Schiller University Jena, Germany)
Walter Fontana (Harvard Medical School, Boston, USA)
Rudolf Freund (Vienna University of Technology, Austria)
Tim Hutton (University College London, UK)
Christian Jacob (University of Calgary, Canada)
Tom Lenaerts (IRIDIA-Universite Libre de Bruxelles, Belgium)
Jian-Qin Liu (ATR, Japan)
Duraid Madina (University of New South Wales, Australia)
Yasunobu Nishida (Toyama Prefectural University, Japan)
Naoaki Ono (ERATO/Osaka University, Japan)
Hiroki Sayama (University of Electro-Communications, Japan)
Barak Shenhav (Weizmann Institute of Science, Israel)
Moshe Sipper (Ben-Gurion University, Israel)
Andre Skusa (University of Bielefeld, Germany)
Pietro Speroni di Fenizio (University of Jena, Germany)
Peter F. Stadler (University of Leipzig, Germany)
Hideaki Suzuki (ATR/NICT, Japan)
Yasuhiro Suzuki (Nagoya University, Japan)
Kazuto Tominaga (Tokyo University of Technology, Japan)
David A. Winkler (CSIRO, Australia)


Important Dates:
Receipt of submissions:    2nd October, 2006
Notification:              15th November, 2006
Final manuscripts due:     End of December, 2006

For further information on this special issue and
instructions for authors, please contact the guest editors.

If you plan a contribution, please notify one the guest editors 
in advance, e.g., by sending a tentative title or abstract.

Hideaki Suzuki: hsuzuki at nict.go.jp
Peter Dittrich: dittrich at minet.uni-jena.de


REFERENCES

(The following references are given as examples. The list is far from
 covering all aspects of artificial chemistries.)

J.-P. Ban^atre and D. Le M'etayer. A new computational model and
 its discipline of programming.  technical report RR-0566, INRIA, 
September
 1986.

G. Berry and G. Boudol. The chemical abstract machine. Theor. Comput. 
Sci.,
 96(1):217-248, 1992.

P. Dittrich, J. Ziegler, and W. Banzhaf. Artificial chemistries - a
 review. Artif. Life, 7(3):225-275, 2001.

M.  Eigen  and  P.  Schuster.   The  hypercycle:   a  principle  of 
 natural  self-organisation, part A. Naturwissenschaften, 64(11):541-565, 
1977.

W. Fontana and L. W. Buss  'The arrival of the fittest':  Toward a theory 
of
 biological organization. Bull. Math. Biol., 56:1-64, 1994.

B. A. Grzybowski, H. A. Stone, and G. M. Whitesides. Dynamic self-assembly
 of magnetized, millimetre-sized objects rotating at a liquid-air
 interface. Nature, 405(6790):1033-1036, 2000.

K. Hosokawa, I. Shimoyama, and H. Miura.  Dynamics of self-
 assembling systems: Analogy with chemical kinetics. Artificial Life,
 1(4):413-427, 1994.

S. Jain and S. Krishna.  A model for the emergence of cooperation, 
interde-
 pendence, and structure in evolving networks. Proc. Natl. Acad. Sci. U.
 S. A., 98(2):543-547, 2001.

Y. Kanada. Combinatorial problem solving using randomized dynamic tun-
 neling on a production system.  In 1995 IEEE International Conference on
 Systems, Man and Cybernetics. Intelligent Systems for the 21st Century, 
vol-
 ume 4, pages 3784-9, New York, NY, 1995. IEEE.

D. Segr'e, D. Lancet, O. Kedem, and Y. Pilpel. Graded autocatalysis
 replication domain (GARD): Kinetic analysis of self-replication in 
mutually catalytic
 sets. Orig. Life Evol. Biosph., 28(4-6):501-514, 1998.

H. Suzuki.  Spacial representation for artificial chemistry based on
 small-world networks.  In Proceedings of the Ninth International 
Conference on the
 Simulation and Synthesis of Living Systems (Artificial Life IX) pages 
507-513, 2004

A. Turing.  A chemical basis for morphogenesis.  Phil. Trans. B, 
237:37-72, 1952.

T. Szuba and A. Stras.  Evaluation of the inference power of a closed 
social
 structure with the help of the random prolog processor. In Fifth
 International Conference on the Practical Application of Prolog, pages 
369-389, 1997.

T. Yamamoto and K. Kaneko. Tile automaton: A model for an architecture of
 a living system. Artif. Life, 5(1):37-76, 1999.

J. Ziegler and W. Banzhaf. Evolving control metabolisms for a robot.
 Artif. Life, 7(2):171 - 190, 2001.






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Peter Dittrich                                                 |
Jena Centre for Bioinformatics (JCB) &                         |
Friedrich-Schiller-University Jena                             |
Department of Mathematics and Computer Science                 |
Bio Systems Analysis Group                                     |
http://www.informatik.uni-jena.de/csb                          |
Ernst-Abbe-Platz 1-4, D-07743 Jena, Germany                    |
Phone: +49 3641 9 46460                                        |
Mobile: +49 163 3925615                                        |
Fax:   +49 3641 9 46302     Office: R. 3401                    |
Email: dittrich at cs.uni-jena.de                                 |
URL:   http://www.informatik.uni-jena.de/~dittrich             |