Artificial Immune System driven evolution in Swarm Chemistry.

Capodieci, Nicola; Hart, Emma; Cabri, Giacomo

Abstract

Morphogenetic engineering represents an interesting field in which models, frameworks and algorithms can be tested in order to study how self-* properties and emergent behaviours can arise in potentially complex and distributed systems. In this field, the morphogenetic model we will refer to is swarm chemistry, since a well known challenge in this dynamical process concerns discovering mechanisms for providing evolution within coalescing systems of particles. These systems consist in sets of moving particles able to self-organise in order to create shapes or geometrical formations that provide robustness towards external perturbations. We present a novel mechanism for providing evo- lutionary features in swarm chemistry that takes inspiration from artificial immune system literature, more specifically regarding idiotypic networks. Starting from a restricted set of chemical recipes, we show that the system evolves to new states, using an autonomous method of detecting new shapes and behaviours free from any human interaction.

Citation

Capodieci, N., Hart, E., & Cabri, G. (2014). Artificial Immune System driven evolution in Swarm Chemistry. In Proceedings of IEEE SASO 2014 (40-49). https://doi.org/10.1109/SASO.2014.16

• Conference Name: IEEE Conference on Self-Organising and Self-Adaptative Systems (SASO)
• Start Date: Sep 8, 2014
• End Date: Sep 12, 2014
• Publication Date: 2014
• Deposit Date: Oct 29, 2014
• Publicly Available Date: May 16, 2017
• Peer Reviewed: Peer Reviewed
• Pages: 40-49
• Book Title: Proceedings of IEEE SASO 2014
• DOI: https://doi.org/10.1109/SASO.2014.16
• Keywords: Artificial Immune Systems; Morphogenetic engineering; distributed systems; swarm chemistry
• Public URL: http://researchrepository.napier.ac.uk/id/eprint/7264
• Publisher URL: http://dx.doi.org/10.1109/SASO.2014.16