title: Spatial-pattern-induced evolution of a self-replicating loop network.
abstract: We study a system of self-replicating loops in which interaction rules between individuals allow competition that leads to the formation of a hypercycle-like network. The main feature of the model is the multiple layers of interaction between loops, which lead to both global spatial patterns and local replication. The network of loops manifests itself as a spiral structure from which new kinds of self-replicating loops emerge at the boundaries between different species. In these regions, larger and more complex self-replicating loops live for longer periods of time, managing to self-replicate in spite of their slower replication. Of particular interest is how micro-scale interactions between replicators lead to macro-scale spatial pattern formation, and how these macro-scale patterns in turn perturb the micro-scale replication dynamics.
authors.affiliation: Department of General Systems Sciences, The Graduate School of Arts and Sciences, University of Tokyo, 3-8-1 Komaba, Tokyo 153-8902, Japan. ksk@sacral.c.u-tokyo.ac.jp
authors.forename: Keisuke
authors.initials: K
authors.lastname: Suzuki
authors.forename: Takashi
authors.initials: T
authors.lastname: Ikegami
mesh_terms: D001185:Artificial Intelligence; D005075:Biological Evolution; D008954:Models, Biological; D008957:Models, Genetic; D009154:Mutation; D010363:Pattern Recognition, Automated; D049490:Systems Biology; D013598:Systems Theory