143 citations · 673 across the 47 of their papers we have counts for
23 papers · 1 filter
Towards Self-Assembling Artificial Neural Networks through Neural Developmental Programs
Elias Najarro, Shyam Sudhakaran, Sebastian Risi
Biological nervous systems are created in a fundamentally different way than current artificial neural networks. Despite its impressive results in a variety of different domains, d…
Learning to Act through Evolution of Neural Diversity in Random Neural Networks
Joachim Winther Pedersen, Sebastian Risi
Biological nervous systems consist of networks of diverse, sophisticated information processors in the form of neurons of different classes. In most artificial neural networks (ANN…
Severe Damage Recovery in Evolving Soft Robots through Differentiable Programming
Kazuya Horibe, Kathryn Walker, Rasmus Berg Palm +2
Biological systems are very robust to morphological damage, but artificial systems (robots) are currently not. In this paper we present a system based on neural cellular automata,…
Goal-Guided Neural Cellular Automata: Learning to Control Self-Organising Systems
Shyam Sudhakaran, Elias Najarro, Sebastian Risi
Inspired by cellular growth and self-organization, Neural Cellular Automata (NCAs) have been capable of "growing" artificial cells into images, 3D structures, and even functional m…
HyperNCA: Growing Developmental Networks with Neural Cellular Automata
Elias Najarro, Shyam Sudhakaran, Claire Glanois +1
In contrast to deep reinforcement learning agents, biological neural networks are grown through a self-organized developmental process. Here we propose a new hypernetwork approach…
Variational Neural Cellular Automata
Rasmus Berg Palm, Miguel González-Duque, Shyam Sudhakaran +1
In nature, the process of cellular growth and differentiation has lead to an amazing diversity of organisms -- algae, starfish, giant sequoia, tardigrades, and orcas are all create…