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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1007/bfb005...
Part of book or chapter of book . 1998 . Peer-reviewed
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DBLP
Conference object . 2021
Data sources: DBLP
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Dynamics of an information-filtering economy

Authors: Jeffrey O. Kephart; James E. Hanson; David W. Levine; Benjamin N. Grosof; Jakka Sairamesh; Richard B. Segal; Steve R. White;

Dynamics of an information-filtering economy

Abstract

Our overall goal is to characterize and understand the dynamic behavior of information economies: very large open economies of automated information agents that are likely to come into existence on the Internet. Here we model a simple information-filtering economy in which broker agents sell selected articles to a subscribed set of consumers. Analysis and simulation of this model reveal the existence of both desirable and undesirable phenomena, and give some insight into their nature and the conditions under which they occur. In particular, efficient self-organization of the broker population into specialized niches can occur when communication and processing costs are neither too high nor too low, but endless price wars can undermine this desirable state of affairs.

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    Average
    influence
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Powered by OpenAIRE graph
Found an issue? Give us feedback
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!
17
Average
Top 10%
Top 10%
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