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Genetic estimation of competitive agents behavior

Authors: Adina Magda Florea;

Genetic estimation of competitive agents behavior

Abstract

The paper presents a multi-agent system that tries to solve the problem of rational exploitation of natural renewable resources by self-interested agents. The particular problem instance is that of several fishing companies trying to catch fish in several fishing banks. The system comprises a set of cognitive agents that represent the companies, are able to build plans and will interact with other companies to ensure the ecological balance of the resources and the achievement of their own plans. The environment is represented by a particular agent with which the companies interact. The agents are using both a symbolic representation and a genetic representation to build plans, to model the evolution of the unpredictable world in which they live and to conduct negotiation. The genetic approach is based on cooperative coadapted species and is used to model the multi-agent world from the point of view of a particular agent.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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