This work uses differentiable simulations and reinforcement learning to design interpretable genetic networks, enabling simulated cells to self-organize into emergent developmental patterns by responding to local chemical and mechanical cues.
- Ramya Deshpande
- Francesco Mottes
- Alma Dal Co
