This paper presents a set of algorithms for trade modeling with cellular automata (CA). The cellular automata simulator developed for this purpose has allowed the study of phenomena that occur within groups of agents that operate in a dynamic resource field. With this cellular automata simulator algorithms have been developed and tested for clustering of agents in agencies and for studying phenomena within agencies. It was thus evident that within agencies the agents try to group in the neighborhood of leading and rich agents with high performance, in order to learn from them the best rules. In terms of hierarchy, the results show that the places in the immediate neighborhood of the agents with leading positions can be occupied only by agents with wealth.
Published in | International Journal of Intelligent Information Systems (Volume 2, Issue 5) |
DOI | 10.11648/j.ijiis.20130205.13 |
Page(s) | 87-93 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2013. Published by Science Publishing Group |
Cellular Automata, Agent-Based Systems, Trade Modeling
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APA Style
Monica Dascalu, Lucian Milea, Gabriela Ivanus, Mihail Teodorescu, Eduard Franti. (2013). Algorithms for Trade Modeling with Agent-Based Systems. International Journal of Intelligent Information Systems, 2(5), 87-93. https://doi.org/10.11648/j.ijiis.20130205.13
ACS Style
Monica Dascalu; Lucian Milea; Gabriela Ivanus; Mihail Teodorescu; Eduard Franti. Algorithms for Trade Modeling with Agent-Based Systems. Int. J. Intell. Inf. Syst. 2013, 2(5), 87-93. doi: 10.11648/j.ijiis.20130205.13
AMA Style
Monica Dascalu, Lucian Milea, Gabriela Ivanus, Mihail Teodorescu, Eduard Franti. Algorithms for Trade Modeling with Agent-Based Systems. Int J Intell Inf Syst. 2013;2(5):87-93. doi: 10.11648/j.ijiis.20130205.13
@article{10.11648/j.ijiis.20130205.13, author = {Monica Dascalu and Lucian Milea and Gabriela Ivanus and Mihail Teodorescu and Eduard Franti}, title = {Algorithms for Trade Modeling with Agent-Based Systems}, journal = {International Journal of Intelligent Information Systems}, volume = {2}, number = {5}, pages = {87-93}, doi = {10.11648/j.ijiis.20130205.13}, url = {https://doi.org/10.11648/j.ijiis.20130205.13}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.20130205.13}, abstract = {This paper presents a set of algorithms for trade modeling with cellular automata (CA). The cellular automata simulator developed for this purpose has allowed the study of phenomena that occur within groups of agents that operate in a dynamic resource field. With this cellular automata simulator algorithms have been developed and tested for clustering of agents in agencies and for studying phenomena within agencies. It was thus evident that within agencies the agents try to group in the neighborhood of leading and rich agents with high performance, in order to learn from them the best rules. In terms of hierarchy, the results show that the places in the immediate neighborhood of the agents with leading positions can be occupied only by agents with wealth.}, year = {2013} }
TY - JOUR T1 - Algorithms for Trade Modeling with Agent-Based Systems AU - Monica Dascalu AU - Lucian Milea AU - Gabriela Ivanus AU - Mihail Teodorescu AU - Eduard Franti Y1 - 2013/10/30 PY - 2013 N1 - https://doi.org/10.11648/j.ijiis.20130205.13 DO - 10.11648/j.ijiis.20130205.13 T2 - International Journal of Intelligent Information Systems JF - International Journal of Intelligent Information Systems JO - International Journal of Intelligent Information Systems SP - 87 EP - 93 PB - Science Publishing Group SN - 2328-7683 UR - https://doi.org/10.11648/j.ijiis.20130205.13 AB - This paper presents a set of algorithms for trade modeling with cellular automata (CA). The cellular automata simulator developed for this purpose has allowed the study of phenomena that occur within groups of agents that operate in a dynamic resource field. With this cellular automata simulator algorithms have been developed and tested for clustering of agents in agencies and for studying phenomena within agencies. It was thus evident that within agencies the agents try to group in the neighborhood of leading and rich agents with high performance, in order to learn from them the best rules. In terms of hierarchy, the results show that the places in the immediate neighborhood of the agents with leading positions can be occupied only by agents with wealth. VL - 2 IS - 5 ER -