Pascal Ballet, Vincent Rodin and Jacques Tisseau.
Immune mechanisms to regulate multi-agent systems.
GECCO'00, Genetic and Evolutionary Computation COnference, pages 33-35,
Las Vegas (USA), 8 July 2000.
Abstract:
We present in this paper the use of immune mechanisms for the regulation of
reactive multi-agents systems (MAS). More precisely, the aim of our work is
to determine how computer scientists can take benefit from immune phenomenon
to auto-regulate agent populations.
This regulation can be made while integrating cell and molecule behaviors
into agent's behaviors. Let us quote for example the mitosis, apoptosis
or differenciation that are essential mechanisms during an immune response.
The work to do or the problem to be solved are seen as foreign substances,
that is antigenic bodies.
The agents represent immuno-qualified cells having for goal the antigen
inhibition. This process must be efficient, that means it must finish the
work (≠ hypo-immune response) and just the work to do (≠ allergy).
Each agent inherit from one or several cell behaviors. Those behaviors are
extracted from immune cells which have well defined roles.
The first consists in detecting the antigen (the work to do), the second in
giving alarm on a large scale, the third in increasing the capacity and the
precision of the response and the fourth in eliminating the antigen. Our agents
use these roles to mime an immune response.
Hereafter we explain, in three criteria, the reasons of the immune response
choice for MAS:
- The immune system is compound with autonomous entities, able to cooperate,
having behaviors, receptors and means of action. Therefore, a cell is very
close to agent concept.
- The immune system is able to divide "self" and "non-self". Like this, it
can detect the work to do among 1020 different patterns. Thus, this
system is flexible and adaptative, what gets an unquestionable advantage in
environments with strong variability (like for aerial images). This number of
possible shapes is very important, but it can be reduce for the need of
simulation.
- The human immune system is quasi-optimal in the power of the answer to
eliminate the antigen, which would allow us a quasi-optimal use of the
computer resources during multi-agents processes.
The regulation of multi-agents system thanks to immunological principles is
few used today. We will begin with the study of the immune concepts we use
as metaphors for the regulation of the agent populations. Then, we show two
examples illustrating the implementation of the immune concepts. They are
dedicated to the image processing coded in levels of gray. Finally, we
conclude on the interests of this immune approach for the design of MAS.
[Ballet00a.pdf]