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Immune System Modeling: The OO Way
Hugues Bersini
CODE/IRIDIA - ULB
CP 194/6
50, av. Franklin Roosevelt
1050 Bruxelles, Belgium
bersini@ulb.ac.be
Abstract.
This paper motivates the use of Object Oriented technologies such as
OO programming languages, UML and Design Patterns in order to facilitate the
development and the communication of immune system software modeling.
The introduction justifies the need for immune computer models at different
levels of abstraction and for various reasons: pedagogy, testing and study of
emergent phenomena and quantitative predictions. Then the benefits allowed by
adopting the OO way are further illustrated by simple examples of UML class,
state and sequence diagrams and instances of Design Patterns such as the
“Bridge” or the “State”, helping to question and to clarify the immune objects
and relationships. Finally an elementary clonal selection model, restricted to B
cells, antibodies and antigens, and fully developed in the OO spirit is presented.
1 Introduction
All scientific disciplines carrying a name that begins with “artificial” (followed by
“life”, “reality”, “intelligence” or “immune system”) are similarly suffering from a
very ambiguous identity. Their line of research tries to find a way somewhere in the
crossroad of engineering (building useful artefacts), natural sciences (biology or psy-
chology - improving the comprehension and prediction of natural phenomena) and
theoretical computer sciences (developing and mastering the algorithmic world).
Accordingly and depending on which of these perspectives receives more support,
they attempt at attracting different kind of scientists and at stimulating different kind
of scientific attitudes. While the “Alife” community is recently re-focusing its atten-
tion on theoretical biology, engaged in the process of re-attracting genuine biologists
in their community, in our more modest AIS community, it is clearly the “engineer-
ing” perspective that has been the most represented and still prevails over the years.
Since the origin of engineering and technology, nature has offered a reserve of inex-
haustible inspirations which have stimulated the development of useful artefacts for
man. Artificial life has led to new computer tools, such as genetic algorithms, Boo-
lean and neural networks, robots learning by experience, cellular machines and others
which create a new vision of IT for the engineer: parallel, adaptable and autonomous.
In this kind of informatics, complex problems are tackled with the aid of simple
mechanisms, but infinitely iterated in time and space. In this kind of informatics, the
