Open-ended evolution (OEE) in artificial life is typically driven by uninterpretable, black-box neural-network complexity metrics, leaving life-like systems disconnected from physical theories of complexity.
Artificial Life
Posted inBiophysics, Genomics, Proteomics, Bioinformatics, Microbiology & Virology, Nanotechnology & SynBio, Origin & Evolution of Life, Press Release
Simultaneous Synthesis Of All 21 Types Of tRNA In Vitro
Collaborative research by the University of Tokyo and RIKEN Center for Biosystems Dynamics Research has led to the development of a new method for simultaneously synthesizing all transfer RNA (tRNA) […]
Posted inGenomics, Proteomics, Bioinformatics, Nanotechnology & SynBio, Origin & Evolution of Life, Status Report
Survival and Evolutionary Adaptation of Populations Under Disruptive Habitat Change: A Study With Darwinian Cellular Automation
The evolution of living beings with continuous and consistent progress toward adaptation and ways to model evolution along principles as close as possible to Darwin’s are important areas of focus […]
Posted inBiophysics, Biosignatures & Paleobiology, Nanotechnology & SynBio, Origin & Evolution of Life, Status Report
An Open-Ended Approach to Understanding Local, Emergent Conservation Laws in Biological Evolution
While fields like Artificial Life have made huge strides in quantifying the mechanisms that distinguish living systems from non-living ones, particular mechanisms remain difficult to reproduce in silico.