Aggressive and Peaceful Strategies in Cellular Resource Space

AUTHOR(S):

Valentine Zavertanyy, Aleksandr Makarenko

TITLE

Aggressive and Peaceful Strategies in Cellular Resource Space

ABSTRACT

The individual-based approach in the modeling of complex adaptive systems named Artificial Life is considered. Such approach allows to deal with an intrinsic adaptation of the system, with an organism influence on its environment and on other organisms, with altering the whole biosphere and eventually its own possibility to exist, i. e. its own fitness. In the Artificial Life research field of digital ecosystems, such approach provides the ability to trace an a posteriori fitness, which can be treated as emergent features of the system like population size, grouping or stability of exhibited behavior. In the work, we explore the model similar to classic Artificial Life models on spatial lattice and discuss relation between combat and peaceful behavior due to available resource in the system. It is introduced heterogeneous resource landscape in its impact on agent’s behavior, and examine it on the notion of species sustainability. The species sustainability is investigated

KEYWORDS

Artificial Life, Agent-Based Modeling, Cooperation, Cellular Space, Evolution Strategies

REFERENCES

[1]. Adamatskii A., Komosinski M. (2005) Artificial Life Models in Software. Springer- Verlag.

[2]. Adami C. (2005) Introduction to Artificial Life. Berlin, Springer.

[3]. Aguilar W., Santamaria-Bonfil G., Froese T., Gershenson C. (2014) The Past, Present, and Future of Artificial Life, Frontiers in Robotics and AI, 10 October 2014, http: //dx.doi.org/10.3389/frobt.2014.00008.

[4]. Aoki K, Feldman M. W. (2014) Evolution of learning strategies in temporally and spatially variable environments: A review of theory. Theoretical population biology, doi:10.1016/j.tpb.2013.10.004.

[5]. Bedau M. A., McCaskill J. S., Packard N. H., Rasmussen, S., Adami C., Green .G. etal. (2000) Open problems in artificial life. Artif. Life 6, pp 363–376, doi:10.1162/106454600300103683, doi:10.3389/frobt.2014.00008.

[6]. Bulgakova T. I., Kalugin O. S., Lyapunov A. A. (1968) On the stability of the simplest model biogeocoenose Problems of Cybernetics. Nauka, Moscow, pp 272-276

[7]. Burtsev M., Turchin P. (2006) Evolution of Cooperative Strategies From First Principles. Nature, vol. 440, pp 1041-1044 (20 April 2006).

[8]. Burtsev M.S. (2004) Tracking the Trajectories of Evolution. Artificial Life. V. 10. 4, pp 397-411.

[9]. Burtsev M.S. (2005) Artificial Life Meets Anthropology: A Case of Aggression in Primitive Societies. In: M. Capcarrere et al. (Eds.): ECAL, LNAI, pp 655 – 664.

[10]. D’Ambrosio D. B., Stanley K. O. (2008) Generative encoding for multiagent learning. In Proceedings of the Genetic and Evolutionary Computation Conference. New York: ACM Press. doi: 10.1145/1389095.1389256.

[11]. Dorin A. (2014) Biological Bits. A Brief Guide to the Ideas and Artefacts of Computational Artificial Life. Animaland, Melbourne.

[12]. Epstein Joshua M., Robert Axtell (1996) Growing artificial societies: social science from the bottom up. Brookings Institution Press. Doi: 10.2307/1060800

[13]. Preston F. W. (1948) The commonness, and rarity, of species. Ecology: Ecological Society of America, pp 185-215.

[14]. Forrest S., Jones T. (1994) Modeling complex adaptive systems with Echo. Complex Systems: Mechanisms of Adaptation. IOS Press, Amsterdam, pp 3-21.

[15]. Gras R, Golestani A, Hendry A. P., Cristescu M. E. (2015) Speciation without Pre-Defined Fitness Functions. PLoS ONE 10(9): e0137838, doi: 10.1371/journal.pone.0137838

[16]. Hraber P. T., Milne B. T. (1997) Community Assembly in a Model Ecosystem. Ecological Modeling, pp 267-285.

[17]. Krivenko S., Burtsev M. (2007) Simulation of the evolution of aging: effects of aggression and kin-recognition. In Advances in Artificial Life, 9th European Conference, ECAL, Lecture Notes in Computer Science, pp 84–92

[18]. Langton C.G. Artificial Life : An Overview. Cambridge, MA: MIT Press. 1997.

[19]. Lindgren K., Nordahl N. G. (1994) Cooperation and Community structure in artificial ecosystems. Artificial Life, 1:15–37.

[20]. Packard N., Langton C.G. (1989) Intrinsic adaptation in a simple model for evolution. Artificial life, Redwood City, Addison- Wesley, CA, pp 141-155

[21]. Penn A. Artificial Life and Society: Philosophies and Tools for Experiencing, Interacting and Managing Real World Complex Adaptive Systems. Proc. Int. Conf. Acai – 2016, Cancun, Mexico. Pp. 26-27.

[22]. Taylor T., Auerbach J. E., Bongard J. teal. A Review of the First 21 Year of Artificial Life on the Web. Artificial Life (USA), MIT, Massacussets. 2016. Vol. 22. N.3, pp. 364- 407.

[23]. Yaeger L. (1994) Computational Genetics, Physiology, Learning, Vision, and Behavior or PolyWord: Life in a New Context. In Langton, C. G. (ed.): Artificial Life III. Addison-Wesley, pp 263-298.

[24]. Wikipedia. Artificial Life. https://en.wikipedia.org/wiki/Artificial_Life

Cite this paper

Valentine Zavertanyy, Aleksandr Makarenko. (2018) Aggressive and Peaceful Strategies in Cellular Resource Space. International Journal of Control Systems and Robotics, 3, 8-21