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Model of a news filtering economyOur model system is an information filtering economy, first described in ref. [Kephart et al., 1998]. It consists of a source agent that publishes news articles, C consumer agents that want to buy articles they are interested in, B broker agents that buy selected articles from the source and resell them to consumers, and a system infrastructure that provides communication and computation services to all agents. A diagram showing part of our model system is shown in Fig. 1. The ellipse at the top represents the source agent, brokers are in the middle, and consumers are at the bottom. Each agent's internal parameters (defined below) are printed inside its ellipse. The system is represented by the rectangle on the left. Solid lines represent the propagation of a sample article through broker 1. Broken lines indicate payment, and are labeled with symbols (explained below) for the amount paid.
The source agent publishes one article at each time step t,
and waits until that article has propagated through the system
before publishing the next. It classifies articles according to its
own internal categorization scheme, assigning
each a category index j when it is offered.
The nature of the categories, and the number J of them, do not change.
We represent this (hidden) classification scheme by a random process
in which an article is assigned category j with fixed probability
Upon receiving an offer, each broker b decides whether or not to buy
the article using its own evaluation method to select which categories
it is ``interested'' in. The broker's evaluation method
is approximated by an
interest vector
When broker b purchases an article, it immediately
sends it to a set of subscribing consumers, paying tranportation
cost
Subscriptions are represented by a
subscription matrix S, where
Each consumer waits for articles to arrive from the brokers it
subscribes to. When a consumer receives one or more copies of an
article, it pays the computation cost
An alternative formulation of the system replaces the consumer's
computational cost Each broker's or consumer's decision-making process may be expressed as an attempt to optimize its utility function, defined as the amount of net ``value'' or ``utility''--however it may be measured--gained by making that particular decision. In the system described here, the expected utility per article for each broker and consumer may be explicitly formulated from the system variables. For consumers, the anticipated value V provides the fundamental benchmark for measuring utility. For brokers, the appropriate measure of utility is profit, defined in the usual way as revenue less expenses. General expressions for consumer utility and broker profit may be found in ref. [Kephart et al., 1998].
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