English

Seeking Open-Ended Evolution in Swarm Chemistry II: Analyzing Long-Term Dynamics via Automated Object Harvesting

Adaptation and Self-Organizing Systems 2018-06-05 v2 Multiagent Systems Neural and Evolutionary Computing

Abstract

We studied the long-term dynamics of evolutionary Swarm Chemistry by extending the simulation length ten-fold compared to earlier work and by developing and using a new automated object harvesting method. Both macroscopic dynamics and microscopic object features were characterized and tracked using several measures. Results showed that the evolutionary dynamics tended to settle down into a stable state after the initial transient period, and that the extent of environmental perturbations also affected the evolutionary trends substantially. In the meantime, the automated harvesting method successfully produced a huge collection of spontaneously evolved objects, revealing the system's autonomous creativity at an unprecedented scale.

Keywords

Cite

@article{arxiv.1804.03304,
  title  = {Seeking Open-Ended Evolution in Swarm Chemistry II: Analyzing Long-Term Dynamics via Automated Object Harvesting},
  author = {Hiroki Sayama},
  journal= {arXiv preprint arXiv:1804.03304},
  year   = {2018}
}

Comments

8 pages, 9 figures, to be published in the ALIFE 2018 proceedings