Abstract
A wide variety of practical problems related to the interaction of agents can be examined using biological metaphors. This paper applies the theory of G-networks to agent systems by considering a biological metaphor based on three types of entities: normal cells C, cancerous or bad cells B, and immune defense agents A which are used to destroy the bad cells B, but which sometimes have the effect of being able to destroy the good cells C as well (autoimmune response). Cells of type C can mutate into cells of Type B, and vice-versa. In the presence of probabilities of correct detection and false alarm on the part of agents of Type A, we examine how the dose of agent A will influence the desired outcome which is that most bad cells B are destroyed while the damage to cells C is limited to an acceptable level. In a second part of the paper we illustrate how a similar model can be used to represent a mixture of agents with the ability to cooperate as well as to compete.
This work is supported by the UK MoD Defense Technology Centre for Data and Information Fusion.
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Gelenbe, E., Kaptan, V., Wang, Y. (2004). Biological Metaphors for Agent Behavior. In: Aykanat, C., Dayar, T., Körpeoğlu, İ. (eds) Computer and Information Sciences - ISCIS 2004. ISCIS 2004. Lecture Notes in Computer Science, vol 3280. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30182-0_67
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DOI: https://doi.org/10.1007/978-3-540-30182-0_67
Publisher Name: Springer, Berlin, Heidelberg
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