Abstract
An artificial immune system approach for artificial chemistries (ACs) based on set rewriting methods is introduced. We model signals which are generated by the execution of rewriting rules in the artificial chemistry. They induce signal patterns which trigger a system response. This response is also based on the rewriting rules of the AC. The latter inhibit or accelerate self-reproducing rewriting instructions and eliminate or inhibit non-self rewriting rules in the AC. Exemplarily, the developed artificial immune system model is integrated into the computational model of Fraglets, an AC which is based on multiset rewriting. Experimental results show the feasibility of this approach.
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Schreckling, D., Marktscheffel, T. (2010). An Artificial Immune System Approach for Artificial Chemistries Based on Set Rewriting. In: Hart, E., McEwan, C., Timmis, J., Hone, A. (eds) Artificial Immune Systems. ICARIS 2010. Lecture Notes in Computer Science, vol 6209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14547-6_20
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DOI: https://doi.org/10.1007/978-3-642-14547-6_20
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