The iterative evolution of an organism creates a rhythmic structure of biological time — a tempo shaped not by clocks, but by cycles of growth, mutation, and emergence. Each iteration carries memory, difference, and possibility, echoing through generative loops that define the organism's form and behavior. Here, development is a choreography of feedback and adaptation, where pattern and variation co-evolve.
Artificial Embryogeny is a computational approach inspired by biological development, where complex algorithmic systems are not explicitly designed but instead grown from minimal, generative instructions. Just as DNA guides the emergence of intricate lifeforms through embryogenesis, this technique leverages developmental processes to evolve structure, behavior, and form.
For this course, we will explore algorithmic techniques rooted in biological poetics — drawing from nature’s logic and aesthetic — to initiate self-organizing, evolving systems. These systems, guided by encoded rules and developmental metaphors, will unfold into complex entities capable of adaptation, transformation, and emergent expression. Through code, simulation, and conceptual exploration, we invite a reimagining of creation — not as construction, but as cultivation — where digital organisms grow, mutate, and evolve within algorithmic ecologies. To engage with this rhythm is to listen to the pulse of artificial life, to see the time interwined into form, and to imagine systems that unfold like organisms — not built, but grown.
http://nn.cs.utexas.edu/downloads/papers/stanley.alife03.pdf