scholarly journals How to Program Artificial Chemistries

Author(s):  
Jens Busch ◽  
Wolfgang Banzhaf
2015 ◽  
pp. 405-438 ◽  
Author(s):  
Wolfgang Banzhaf ◽  
Lidia Yamamoto

2018 ◽  
Author(s):  
Penelope Faulkner Rainford ◽  
Angelika Sebald ◽  
Susan Stepney

Author(s):  
Wolfgang Banzhaf ◽  
Lidia Yamamoto

1998 ◽  
Vol 4 (1) ◽  
pp. 25-40 ◽  
Author(s):  
Jens Breyer ◽  
Jörg Ackermann ◽  
John McCaskill

Recently, new types of coupled isothermal polynucleotide amplification reactions for the investigation of in vitro evolution have been established that are based on the multi-enzyme 3SR reaction. Microstructured thin-film open bioreactors have been constructed in our laboratory to run these reactions spatially resolved in flow experiments. Artificial DNA/RNA chemistries close to the in vitro biochemistry of these systems have been developed, which we have studied in computer simulations in configurable hardware (NGEN). These artificial chemistries are described on the level of individual polynucleotide molecules, each with a defined sequence, and their complexes. The key feature of spatial pattern formation provides a weak stabilization of cooperative catalytic properties of the evolving molecules. Of great interest is the step to include extended self-assembly processes of flexible structures—allowing the additional stabilization of cooperation through semipermeable, flexible, self-organizing membrane boundaries. We show how programmable matter simulations of experimentally relevant molecular in vitro evolution can be extended to include the influence of self-assembling flexible membranes.


2004 ◽  
Vol 97-98 ◽  
pp. 43-50 ◽  
Author(s):  
Wolfgang Banzhaf

In this contribution we consider constructive dynamical systems, taking one particular Artificial Chemistry as an example. We argue that constructive dynamical systems are in fact widespread in combinatorial spaces of Artificial Chemistries.


2007 ◽  
Vol 13 (3) ◽  
pp. 223-247 ◽  
Author(s):  
Kazuto Tominaga ◽  
Tooru Watanabe ◽  
Keiji Kobayashi ◽  
Masaki Nakamura ◽  
Koji Kishi ◽  
...  

Artificial chemistries are mainly used to construct virtual systems that are expected to show behavior similar to living systems. In this study, we explore possibilities of applying an artificial chemistry to modeling natural biochemical systems—or, to be specific, molecular computing systems—and show that it may be a useful modeling tool for molecular computation. We previously proposed an artificial chemistry based on string pattern matching and recombination. This article first demonstrates that this artificial chemistry is computationally universal if it has only rules that have one reactant or two reactants. We think this is a good property of an artificial chemistry that models molecular computing, because natural elementary chemical reactions, on which molecular computing is based, are mostly unimolecular or bimolecular. Then we give two illustrative example models for DNA computing in our artificial chemistry: one is for the type of computation called the Adleman-Lipton paradigm, and the other is for a DNA implementation of a finite automaton. Through the construction of these models we observe preferred properties of the artificial chemistry for modeling molecular computing, such as having no spatial structure and being flexible in choosing levels of abstraction.


2015 ◽  
pp. 345-372
Author(s):  
Wolfgang Banzhaf ◽  
Lidia Yamamoto

Author(s):  
Wolfgang Banzhaf ◽  
Lidia Yamamoto

Author(s):  
Penelope Faulkner ◽  
Mihail Krastev ◽  
Angelika Sebald ◽  
Susan Stepney

2001 ◽  
Vol 7 (2) ◽  
pp. 171-190 ◽  
Author(s):  
Jens Ziegler ◽  
Wolfgang Banzhaf

This article demonstrates a new method of programming artificial chemistries. It uses the emerging capabilities of the system's dynamics for information-processing purposes. By evolution of metabolisms that act as control programs for a small robot one achieves the adaptation of the internal metabolic pathways as well as the selection of the most relevant available exteroceptors. The underlying artificial chemistry evolves efficient information-processing pathways with most benefit for the desired task, robot navigation. The results show certain relations to such biological systems as motile bacteria.


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