Volume 2, Issue 5, October 2013, Page: 87-93
Algorithms for Trade Modeling with Agent-Based Systems
Monica Dascalu, Politehnica University of Bucharest, Romania
Lucian Milea, Solaris Consult S.R.L., Bucharest, Romania
Gabriela Ivanus, Politehnica University of Bucharest, Romania
Mihail Teodorescu, Research Institute for Artificial Intelligence, Bucuresti, Romania
Eduard Franti, Research Institute for Artificial Intelligence, Bucuresti, Romania
Received: Oct. 7, 2013;       Published: Oct. 30, 2013
DOI: 10.11648/j.ijiis.20130205.13      View  2667      Downloads  79
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.
Cellular Automata, Agent-Based Systems, Trade Modeling
To cite this article
Monica Dascalu, Lucian Milea, Gabriela Ivanus, Mihail Teodorescu, Eduard Franti, Algorithms for Trade Modeling with Agent-Based Systems, International Journal of Intelligent Information Systems. Vol. 2, No. 5, 2013, pp. 87-93. doi: 10.11648/j.ijiis.20130205.13
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