Mobile agent evolution computing
Information Sciences, 137 (1-4):
53--73 (2001)Zusammenfassung
The ecosystem is an evolutionary result of natural
laws. Food web (or food chain) embeds a set of
computation rules of natural balance. Based on the
concepts of food web, one of the laws that we may learn
from the natural besides neural networks and genetic
algorithms, we propose a theoretical computation model
for mobile-agent evolution on the Internet. We define
an agent niche overlap graph and agent evolution
states. We also propose a set of algorithms, which is
used in our multimedia search programs, to simulate
agent evolution. Agents are cloned to live on a remote
host station based on three different strategies: the
brute force strategy, the semi-brute force strategy,
and the selective strategy. Evaluations of different
strategies are discussed. Guidelines of writing
mobile-agent programs are proposed. The technique can
be used in distributed information retrieval which
allows the computation load to be added to servers, but
significantly reduces the traffic of network
communication. In the literature of software agents, it
is hard to find other similar models. The results of
this research only address a small portion of the ice
field. We hope that this problem would be further
studied in the societies of network communications,
multimedia information retrieval, and intelligent
systems on the Internet.