Exploring Emergence in Artificial Life
Over the past week I’ve been digesting concepts from Emergence in Artificial Life by Carlos Gershenson, my professor for Modern Complexity Theory.1 In the paper, Gershenson provides a formal definition of emergence grounded in Claude Shannon’s measure of information. He also defines self-organization as being anti-correlated with emergence, and complexity as being equal to a normalized balance between emergence and self-organization.
In order to solidify my understanding of key concepts in the paper, I’m applying them to an analysis of emergent properties in Bitcoin as my contribution to this week’s class discussion. I’ll be sharing this analysis as a short essay next week.
Generally I’ve found concepts from systems science to be much more immediately useful for my purposes than those from complexity science. Early into this new semester, I’m already starting to get a feel for what I’ve been missing out on by neglecting the world of complexity.
Gershenson, C. (2023). Emergence in Artificial Life. Artificial Life, 29(2), 153–167. https://doi.org/10.1162/artl_a_00397