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Artificial Immune System driven evolution in Swarm Chemistry.

Capodieci, Nicola; Hart, Emma; Cabri, Giacomo


Nicola Capodieci

Giacomo Cabri


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.

Presentation Conference Type Conference Paper (Published)
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
Keywords Artificial Immune Systems; Morphogenetic engineering; distributed systems; swarm chemistry;
Public URL
Publisher URL
Contract Date May 16, 2017


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