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Individual-based modelling

Example of environment state
Fig. 1. An example of the environment state.

The term individual-based modelling describes a group of simulation, in which the local rules of interaction between elements of the system are specified, and then an evolution of the system consisting of many such elements is investigated by computer simulation. Using this approach, a complex global behaviour of a model is obtained as a result of many simultaneous, distributed in space, local and simple interactions.

Individual-based models are natural for many physical, chemical or biological systems, whose behaviour is a result of interactions of many active elements distributed in space. They could be especially beneficial when, besides a mere numerical agreement with a physical system, the model should map its structure and topology. For such systems, individual-based modelling can be an attractive substitute for models based on differential equations apparatus. Moreover individual-based approach makes it possible to work with models of complex biological systems, which would be impossible even to formulate in traditional mathematical frameworks. Cellular automata, lattice gas automata, molecular dynamics and particle models are well known formal context for individual-based modelling.

The DigiHive environment

The DigiHive environment is an original, artificial, complete, low level, and closed environment consisting of space, moving objects, and rules which govern their interactions. The environment operates on two levels. On the first level, entities move and collide. Collisions result in rebounding off entities or randomly changing their internal structures. On the second level some structures of entities are capable of inducing specific changes in other entities. Types of the changes are encoded in structures of entities in simplified Prolog language.

The simulation can start from any initial configuration of entities thus allowing to model various systems. In Fig. 1 example of the environment state is presented. Circles represent basic constituent objects called particles. Particles can bound together forming a complex of particles - in Fig. 1 showed as filled circles.

Development history

Inspired by ideas contained in Holland and Martinez publications [1, 11], the first version of the environment was implemented [3, 5]. In the following papers: [2, 4, 9] various simulation results were then described. Due to serious limitations described in papers: [12, 14, 18] environment wasn't well suited to perform simulation from the artificial life field.

In 2006, the new environment was designed and implemented. The main improvements are:

  • continous space instead of tesselation of squares,
  • hexagonal shape of entities instead of square one,
  • horizontal and vertical bonds between entities instead horizontal only,
  • programs are encoded by internal structures of complexes,
  • programs are written in a declarative language (simplified Prolog), which is less vulnerable to small fluctuations
The description of the environment and the simulation results are presented in the following papers: [6, 7, 8, 10, 12, 13, 14, 15, 16, 17, 18].

Contact us

Please send any question to: Rafal.Sienkiewicz@eti.pg.gda.pl. Any comments and suggestion are welcome.

References
[1]Holland J., 1976, Studies on the spontaneous emergence of self-replicating systems using cellular automata and formal grammars. in: Lindenmayer A., Rozenberg G. (eds.), Automata, Languages, Development. Amsterdam: North-Holland, pp.385-404.
[2]Jedruch W., 1997, Programming environment for molecular modelling of complex systems,, Wydawnictwo Politechniki Gdańskiej. Gdańsk (in Polish).
[3]Jędruch W., Barski M., 1990, Experiments with a universe for molecular modelling of biological processes., BioSystems, v. 24, pp. 99-117.
[4]Jędruch W., Gramza M., 2001, An individual-based model of self-reproduction system, TASK Quaterly, v.5, no. 3, pp. 1-15.
[5]Jędruch W., Sampson J., 1987, A universe for molecular modelling of self-replication., Biosystems 20, 329-340.
[6]Jędruch W., Sienkiewicz R., 2006, Modelowanie indywiduowe, Aplikacje rozproszone i systemy internetowe, Kask Book, pp. 241-252, Gdańsk University of Technology, Gdańsk, Poland, 2006
[7]Jędruch W., Sienkiewicz R., 2007, Inteligencja zespołowa, Kowalczuk Z., Wiszniewski B (Eds.), Inteligentne wydobywanie informacji w celach diagnostycznych, PWNT 2007
[8]Jędruch W., Sienkiewicz R., 2008, Modelowanie systemów samoreprodukujących się , Metody informatyki stosowanej, 16(3):135—147
[9]Jędruch W., Waniewski J., 1994, Distributed modelling of cell population. Appl. Math. and Compp. Sci., t. 4, nr. 2, 193-202.
[10]Knitter S., 2006, Badanie dynamiki systemów samoreprodukujących się w sztucznym środowisku, Master's Thesis, WETI
[11]Martinez M., 1979, An automaton analogue of unicellularity., BioSystems, v.11, pp.133-159.
[12]Sienkiewicz R., Jędruch W., 2004, Self-organization in an artificial environment, Proceedings of an VI International Conference on Artificial Intelligence AI-19'2004, Nr 23, pp 81-88, Siedlce, Poland.
[13]Sienkiewicz R., Jędruch W., 2006, The universe for individual based modelling, Tech. Report 11/2006/ETI
[14]Sienkiewicz R., 2007, A new language in an environment of artificial life modeling, D. Rutkowska (Eds.): PD FCCS'2007: 3rd Polish and International PD Forum-Conference on Computer Science (in Polish), Smardzewice-Łódź, Poland
[15]Sienkiewicz R., Jędruch W., 2007, An artificial environment for simulation of emergent behaviour, B. Bieliczyński et al. (Eds.): ICANNGA 2007, Part I, LNCS 4431, pp. 386-393
[16]Sienkiewicz R., 2009, Experiments with the universal constructor in the DigiHive environment, Artificial Life: Borrowing from Biology, 4th Australian Conference, ACAL 2009, Melbourne, Australia, December 1-4, 2009, LNAI 5865, pp. 106-115
[17]Sienkiewicz R., Jędruch W., 2009, The universal constructor in the DigiHive environment, Proceedings of 10th European Conference on Artificial Life, ECAL 2009, LNCS 5778, pp. 178-186
[18]Sienkiewicz R., 2010, The particle methods for simulation of self-organization phenomena, PhD thesis, WETI
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