![](bg4.png)
- Declare the purchase impossible and notify the
customer accordingly, see figure (8).
When the attempt at completing a purchase is
successful, then the Buyer agent sends messages to
customer. The situation is slightly more complicated
when the attempt was unsuccessful and purchase
was not deemed impossible. Then the Buyer agent
cancels current reservations and return to price
negotiations.
Figure 8: State diagram of the Buyer agent.
3 WHY MOBILE AGENT IN THE
SYSTEM?
Scripts The agent mobility in E-commerce system
plays an important role and provides significant
benefits. Let us start by considering someone who,
sitting behind a slow Internet connection (which is
not an uncommon situation), tries to participate in an
E-auction (Bejar & Juan, 2001). In this case it is
almost impossible to be sure that ones bid:
(1) Reaches E-auction server in time (Tamma et al
2002). (2) Is sufficiently large to outbid opponents
that have been bidding while connected over a fast
link (information about auction progress as well as
our responses may not be able to reach their
destinations sufficiently fast). Here, network-caused
delays can be significant for the outcome of
negotiations (purchase of the desired product may be
prevented).
Obviously, problems described here can be avoided
if an agent representing user is located at the same
server where the negotiations take place with assume
that an agent is capable of autonomously completing
the requested task (Artikis et al, 2001); resulting in
offers being made fast enough to efficiently
participate in price negotiations.
4 CONCLUSION
This paper discusses ecommerce agent system that
uses mobile agent technologies for implementing
flexible automated negotiations. After presenting an
overview of the proposed system by using UML
diagrams, the attention is focused on questions
involved in agent mobility. I have argued that agent
mobility is the most optimal solution for the e-
commerce model considered here. Finally I have
discussed why there is no simple solution to the
problem of finding the optimal offer when multiple
agents negotiate prices within multiple e-stores and
thus why this solution is as optimal as any other.
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Trastour, D., Bartolini, C., and Preist, C. 2002. Semantic
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Bejar, J., and Juan, A., 2002. To bid or not to bid agent
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Tamma, V., Wooldridge, M., Dickinson, I., 2002. An
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Artikis, F. Guerin, and J. Pitt 2001. Integrating interaction
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