Artificial chemistry

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An artificial chemistry [1] [2] [3] is a chemical-like system that usually consists of objects, called molecules, that interact according to rules resembling chemical reaction rules. Artificial chemistries are created and studied in order to understand fundamental properties of chemical systems, including prebiotic evolution, as well as for developing chemical computing systems. Artificial chemistry is a field within computer science wherein chemical reactions—often biochemical ones—are computer-simulated, yielding insights on evolution, self-assembly, and other biochemical phenomena. The field does not use actual chemicals, and should not be confused with either synthetic chemistry or computational chemistry. Rather, bits of information are used to represent the starting molecules, and the end products are examined along with the processes that led to them. The field originated in artificial life but has shown to be a versatile method with applications in many fields such as chemistry, economics, sociology and linguistics.

Contents

Formal definition

An artificial chemistry is defined in general as a triple (S,R,A). In some cases it is sufficient to define it as a tuple (S,I).

Types of artificial chemistries

Important concepts

History of artificial chemistries

Artificial chemistries emerged as a sub-field of artificial life, in particular from strong artificial life. The idea behind this field was that if one wanted to build something alive, it had to be done by a combination of non-living entities. For instance, a cell is itself alive, and yet is a combination of non-living molecules. Artificial chemistry enlists, among others, researchers that believe in an extreme bottom-up approach to artificial life. In artificial life, bits of information were used to represent bacteria or members of a species, each of which moved, multiplied, or died in computer simulations. In artificial chemistry bits of information are used to represent starting molecules capable of reacting with one another. The field has pertained to artificial intelligence by virtue of the fact that, over billions of years, non-living matter evolved into primordial life forms which in turn evolved into intelligent life forms.

Important contributors

The first reference about Artificial Chemistries come from a Technical paper written by John McCaskill . [4] Walter Fontana working with Leo Buss then took up the work developing the AlChemy model [5] . [6] The model was presented at the second International Conference of Artificial Life. In his first papers he presented the concept of organization, as a set of molecules that is algebraically closed and self-maintaining. This concept was further developed by Dittrich and Speroni di Fenizio into a theory of chemical organizations [7] . [8]

Two main schools of artificial chemistries have been in Japan and Germany. In Japan the main researchers have been Takashi Ikegami , [9] [10] Hideaki Suzuki [11] [12] and Yasuhiro Suzuki [13] . [14] In Germany, it was Wolfgang Banzhaf, who, together with his students Peter Dittrich and Jens Ziegler, developed various artificial chemistry models. Their 2001 paper 'Artificial Chemistries - A Review' [3] became a standard in the field. Jens Ziegler, as part of his PhD thesis, proved that an artificial chemistry could be used to control a small Khepera robot . [15] Among other models, Peter Dittrich developed the Seceder model which is able to explain group formation in society through some simple rules. Since then he became a professor in Jena where he investigates artificial chemistries as a way to define a general theory of constructive dynamical systems.

Applications of artificial chemistries

Artificial Chemistries are often used in the study of protobiology, in trying to bridge the gap between chemistry and biology. A further motivation to study artificial chemistries is the interest in constructive dynamical systems. Yasuhiro Suzuki has modeled various systems such as membrane systems, signaling pathways (P53), ecosystems, and enzyme systems by using his method, abstract rewriting system on multisets (ARMS).

In the 1994 science-fiction novel Permutation City by Greg Egan, brain-scanned emulated humans known as Copies inhabit a simulated world which includes the Autoverse, an artificial life simulator based on a cellular automaton complex enough to represent the substratum of an artificial chemistry. Tiny environments are simulated in the Autoverse and filled with populations of a simple, designed lifeform, Autobacterium lamberti. The purpose of the Autoverse is to allow Copies to explore the life that had evolved there after it had been run on a significantly large segment of the simulated universe (referred to as "Planet Lambert").

See also

Related Research Articles

Chemistry Scientific discipline

Chemistry is the scientific study of the properties and behavior of matter. It is a natural science that covers the elements that make up matter to the compounds composed of atoms, molecules and ions: their composition, structure, properties, behavior and the changes they undergo during a reaction with other substances.

Computational chemistry is a branch of chemistry that uses computer simulation to assist in solving chemical problems. It uses methods of theoretical chemistry, incorporated into computer programs, to calculate the structures and properties of molecules, groups of molecules, and solids. It is necessary because, apart from relatively recent results concerning the hydrogen molecular ion, the quantum many-body problem cannot be solved analytically, much less in closed form. While computational results normally complement the information obtained by chemical experiments, it can in some cases predict hitherto unobserved chemical phenomena. It is widely used in the design of new drugs and materials.

The following outline is provided as an overview of and topical guide to chemistry:

Physical science is a branch of natural science that studies non-living systems, in contrast to life science. It in turn has many branches, each referred to as a "physical science", together called the "physical sciences".

Quantum chemistry, also called molecular quantum mechanics, is a branch of chemistry focused on the application of quantum mechanics to chemical systems. Understanding electronic structure and molecular dynamics using the Schrödinger equations are central topics in quantum chemistry.

Theoretical chemistry Academic field

Theoretical chemistry is the branch of chemistry which develops theoretical generalizations that are part of the theoretical arsenal of modern chemistry: for example, the concepts of chemical bonding, chemical reaction, valence, the surface of potential energy, molecular orbitals, orbital interactions, and molecule activation.

<i>Permutation City</i> 1994 science fiction novel by Greg Egan

Permutation City is a 1994 science-fiction novel by Greg Egan that explores many concepts, including quantum ontology, through various philosophical aspects of artificial life and simulated reality. Sections of the story were adapted from Egan's 1992 short story "Dust", which dealt with many of the same philosophical themes. Permutation City won the John W. Campbell Award for the best science-fiction novel of the year in 1995 and was nominated for the Philip K. Dick Award the same year. The novel was also cited in a 2003 Scientific American article on multiverses by Max Tegmark.

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Molecular modelling Discovering chemical properties by physical simulations

Molecular modelling encompasses all methods, theoretical and computational, used to model or mimic the behaviour of molecules. The methods are used in the fields of computational chemistry, drug design, computational biology and materials science to study molecular systems ranging from small chemical systems to large biological molecules and material assemblies. The simplest calculations can be performed by hand, but inevitably computers are required to perform molecular modelling of any reasonably sized system. The common feature of molecular modelling methods is the atomistic level description of the molecular systems. This may include treating atoms as the smallest individual unit, or explicitly modelling protons and neutrons with its quarks, anti-quarks and gluons and electrons with its photons.

Force field (chemistry) Concept on molecular modeling

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Spartan (chemistry software)

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Physical organic chemistry, a term coined by Louis Hammett in 1940, refers to a discipline of organic chemistry that focuses on the relationship between chemical structures and reactivity, in particular, applying experimental tools of physical chemistry to the study of organic molecules. Specific focal points of study include the rates of organic reactions, the relative chemical stabilities of the starting materials, reactive intermediates, transition states, and products of chemical reactions, and non-covalent aspects of solvation and molecular interactions that influence chemical reactivity. Such studies provide theoretical and practical frameworks to understand how changes in structure in solution or solid-state contexts impact reaction mechanism and rate for each organic reaction of interest.

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Artificial life Field of study

Artificial life is a field of study wherein researchers examine systems related to natural life, its processes, and its evolution, through the use of simulations with computer models, robotics, and biochemistry. The discipline was named by Christopher Langton, an American theoretical biologist, in 1986. In 1987 Langton organized the first conference on the field, in Los Alamos, New Mexico. There are three main kinds of alife, named for their approaches: soft, from software; hard, from hardware; and wet, from biochemistry. Artificial life researchers study traditional biology by trying to recreate aspects of biological phenomena.

Multi-state modeling of biomolecules refers to a series of techniques used to represent and compute the behaviour of biological molecules or complexes that can adopt a large number of possible functional states.

References

  1. 1 2 W. Banzhaf and L. Yamamoto. Artificial Chemistries, MIT Press, 2015.
  2. ↑ P. Dittrich. Artificial chemistry (AC) In A. R. Meyers (ed.), Computational Complexity: Theory, Techniques, and Applications, pp. 185-203, Springer, 2012.
  3. 1 2 P. Dittrich, J. Ziegler, and W. Banzhaf. Artificial chemistries — A review. Artificial Life, 7(3):225–275, 2001.
  4. ↑ J.S.McCaskill. Polymer chemistry on tape: A computational model for emergent genetics. Technical report, MPI for Biophysical Chemistry, 1988.
  5. ↑ W. Fontana. Algorithmic chemistry. In C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, editors, Artificial Life II, pages 159–210. Westview Press, 1991.
  6. ↑ W. Fontana and L. Buss. “The arrival of the fittest”: Toward a theory of biological organization. Bulletin of Mathematical Biology, 56(1):1–64, 1994.
  7. ↑ P. Dittrich, P. Speroni di Fenizio. Chemical Organization Theory. Bulletin of Mathematical Biology (2007) 69: 1199:1231.
  8. ↑ P. Speroni di Fenizio. Chemical Organization Theory. PhD thesis, Friedrich Schiller University Jena, 2007.
  9. ↑ T. Ikegami and T. Hashimoto. Active mutation in self-reproducing networks of machines and tapes. Artificial Life, 2(3):305–318, 1995.
  10. ↑ T. Ikegami and T.Hashimoto. Replication and diversity in machine-tape coevolutionary systems. In C. G. Langton and K. Shimohara, editors, Artificial Life V, pages 426–433. MIT Press, 1997.
  11. ↑ H.Suzuki. Models for the conservation of genetic information with string-based artificial chemistry. In W. Banzhaf, J. Ziegler, T. Christaller, P. Dittrich, and J. T. Kim, editors, Advances in Artificial Life, volume 2801 of Lecture Notes in Computer Science, pages 78–88. Springer, 2003.
  12. ↑ H. Suzuki. A network cell with molecular agents that divides from centrosome signals. Biosystems, 94(1-2):118–125, 2008.
  13. ↑ Y. Suzuki, J. Takabayashi, and H. Tanaka. Investigation of tritrophic interactions in an ecosystem using abstract chemistry. Artificial Life and Robotics, 6(3):129–132, 2002.
  14. ↑ Y. Suzuki and H. Tanaka. Modeling p53 signaling pathways by using multiset processing. In G. Ciobanu, G. Pa ̆un, and M. J. Pérez-Jiménez, editors, Applications of Membrane Computing, Natural Computing Series, pages 203–214. Springer, 2006.
  15. ↑ J.Ziegler and W.Banzhaf. Evolving control metabolisms for a robot. ArtificialLife, 7(2):171–190, 2001.
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