A Method of Representing Cyclic Program Structures in Artificial Chemistry Model
E. A. Kolchugina, D. Sci., Professor, email@example.com, Penza State University, Penza, 440026, Russian Federation
Corresponding author: Elena A. Kolchugina, D. Sci., Professor, Penza State University, Penza, 440026, Russian Federation E-mail: firstname.lastname@example.org
Received on November 24, 2022
Accepted on November 24, 2022
The need for automation of software development processes makes it necessary to search for forms of program representation that can undergo automatic transformations without violating the integrity and semantic significance of the results of such transformations. Previously, we have proposed a notation for programs that permits the use of automatic transformation methods, namely methods of evolutionary development used, in particular, in genetic programming. But we have considered only linear and tree-like structures. In this article, we expand the list of available types of structures by adding cyclic structures, as well as complex structural compositions obtained by combining structures of simpler types. We also propose a rule excluding possible anomalies with cyclic structures representation. In general, the proposed methods are based on the concept of artificial chemistry, where programs are considered as analogues of molecules, and program transformations are considered as analogs of reactions. We illustrate the application of proposed notation using examples of the Kekule formula and the cyclic program, automatically obtained in our previous studies. The results obtained demonstrate that the proposed notation and methods make it possible to compose formulas representing computational structures of various and even mixed types.
Keywords: artificial chemistry, artificial molecules structure, cyclic and complex structures representation, angle brackets notation
Kol'chugina E. A. A Method of Representing Cyclic Program Structures in Artificial Chemistry Model, Programmnaya Ingeneria, 2023, vol. 14, no. 2, pp. 77—81. DOI: 10.17587/prin.14.77-81
- Kol'chugina E. A. Spontaneous Emergence of Programs from "Primordial Soup" of Functions in Distributed Computer Systems, Automatic Control and Computer Sciences, 2018, vol. 52, no. 1, pp. 40—48. DOI: 10.3103/S0146411618010054.
- Eigen M., Schuster P. The Hypercycle: A Principle of Natural Self-Organization, Berlin-Heidelberg-New York, Springer-Verlag, 1979, 98 p.
- Kol'chugina E. A. Model reproduction of non-equilibrium thermodynamics principles as a means to provide software self-development, IOP Conference Series: Materials Science and Engineering; III International Scientific Conference: Modernization, Innovations, Progress: Advanced Technologies in Material Science, Mechanical and Automation Engineering (MIP-III2021), 29th—30th April 2021, Krasnoyarsk, Russian Federation, 2021, vol. 1155, p. 012054. DOI: 10.1088/1757-899X/1155/1/012054.
- Anchordoqui L. A., Chudnovsky E. M. Can Self-Replicating Species Flourish in the Interior of a Star? Letters In High Energy Physics, 2020, vol. 2020, LHEP-166, pp. 1—4. DOI: 10.31526/ LHEP.2020.166.
- Kol'chugina E. A. Self-Synthesis of Programs Based on Artificial Chemistry Model, Programmnaya Ingeneria, 2022, vol. 13, no. 9, pp. 440—448. DOI: 10.17587/prin.13.440-448.
- Dittrich P., Ziegler J., Banzhaf W. Artificial Chemistries — A Review, Artificial Life, 2001, vol. 7, no 3, pp. 225—275. DOI: 10.1162/106454601753238636.
- Banzhaf W., Yamamoto L. Artificial Chemistries, Cambridge, Massachusetts; London, England, The MIT Press, 2015, 576 p.
- Church A. An Unsolvable Problem of Elementary Number Theory, American Journal of Mathematics, Apr. 1936, vol. 58, no. 2, pp. 345—363.
- Holland J. H. Building Blocks, Cohort Genetic Algorithms, and Hyperplane-Defined Functions, Evolutionary Computations, 2000, vol. 8, no. 4, pp. 373—391. DOI: 10.1162/106365600568220.
- Mitchell M. Introduction to Genetic Algorithms, Cambridge, Massachusetts; London, England, A Bradford Book the MIT Press, 1999, 158 p.
- Gladkov L. A., Kurejchik V. V., Kurejchik V. M. Geneticheskie algoritmy / Eds V. M. Kurejchik, 2-nd edition, corrected and expanded, Moscow, Fizmatlit, 2006, 320 p. (in Russian).
- Koza J. R., Bennett F. H., Andre D., Keane M. A. Genetic Programming: Biologically Inspired Computation That Creatively Solves Non-trivial Problems, Evolution as Computation. Natural Computing Series / Eds L. F. Landweber, E. Winfree, Springer, Berlin, Heidelberg, 2002, pp. 95—124. DOI: 10.1007/978-3-642-55606-7_5.