Paper Info
Title
Seeking Open-Ended Evolution In Swarm Chemistry Ii: Analyzing Long-Term Dynamics Via Automated Object Harvesting
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.
Year
DOI
Venue
2018
10.1162/isal_a_00018
2018 CONFERENCE ON ARTIFICIAL LIFE (ALIFE 2018)
Field
DocType
Volume
Swarm behaviour,Artificial intelligence,Evolutionary dynamics,Mathematics,Machine learning
Journal
abs/1804.03304
Citations 
PageRank 
References 
1
0.37
0
Authors
1
Name
Order
Citations
PageRank
Hiroki Sayama131949.14