# Towards Self-Assembling Artificial Neural Networks through Neural Developmental Programs

arXiv: https://arxiv.org/abs/2307.08197 · HTML: https://mlsanity.com/paper/2307.08197/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 44 references that are in the map.
- First posted on arXiv 17 Jul 2023.

## Builds on (most cited first, 15 of 15)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [Semi-Supervised Classification with Graph Convolutional Networks](https://mlsanity.com/paper/1609.02907/) (2016)
- [Decision Transformer: Reinforcement Learning via Sequence Modeling](https://mlsanity.com/paper/2106.01345/) (2021)
- [HyperNetworks](https://mlsanity.com/paper/1609.09106/) (2016)
- [Evolution Strategies as a Scalable Alternative to Reinforcement Learning](https://mlsanity.com/paper/1703.03864/) (2017)
- [Behavioral Cloning from Observation](https://mlsanity.com/paper/1805.01954/) (2018)
- [HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning](https://mlsanity.com/paper/2201.04182/) (2022)
- [Growing 3D Artefacts and Functional Machines with Neural Cellular Automata](https://mlsanity.com/paper/2103.08737/) (2021)
- [Collective Intelligence for Deep Learning: A Survey of Recent Developments](https://mlsanity.com/paper/2111.14377/) (2021)
- [Learning Graph Cellular Automata](https://mlsanity.com/paper/2110.14237/) (2021)
- [When, where, and how to add new neurons to ANNs](https://mlsanity.com/paper/2202.08539/) (2022)
- [HyperNCA: Growing Developmental Networks with Neural Cellular Automata](https://mlsanity.com/paper/2204.11674/) (2022)
- [Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration](https://mlsanity.com/paper/2304.12214/) (2023)
- [A Minimal Developmental Model Can Increase Evolvability in Soft Robots](https://mlsanity.com/paper/1706.07296/) (2017)

## Built on by (most cited first, 17 of 17)

- [From Text to Life: On the Reciprocal Relationship between Artificial Life and Large Language Models](https://mlsanity.com/paper/2407.09502/) (2024)
- [Heuristically Adaptive Diffusion-Model Evolutionary Strategy](https://mlsanity.com/paper/2411.13420/) (2024)
- [Structurally Flexible Neural Networks: Evolving the Building Blocks for General Agents](https://mlsanity.com/paper/2404.15193/) (2024)
- [Evolving Self-Assembling Neural Networks: From Spontaneous Activity to Experience-Dependent Learning](https://mlsanity.com/paper/2406.09787/) (2024)
- [Growing Artificial Neural Networks for Control: the Role of Neuronal Diversity](https://mlsanity.com/paper/2405.08510/) (2024)
- [Modular Growth of Hierarchical Networks: Efficient, General, and Robust Curriculum Learning](https://mlsanity.com/paper/2406.06262/) (2024)
- [Evolved Developmental Artificial Neural Networks for Multitasking with Advanced Activity Dependence](https://mlsanity.com/paper/2407.10359/) (2024)
- [pyhgf: A neural network library for predictive coding](https://mlsanity.com/paper/2410.09206/) (2024)
- [Growing Reservoirs with Developmental Graph Cellular Automata](https://mlsanity.com/paper/2508.08091/) (2025)
- [Hypernetworks That Evolve Themselves](https://mlsanity.com/paper/2512.16406/) (2025)
- [Evolving Reservoirs for Meta Reinforcement Learning](https://mlsanity.com/paper/2312.06695/) (2023)
- [Bio-Inspired Plastic Neural Networks for Zero-Shot Out-of-Distribution Generalization in Complex Animal-Inspired Robots](https://mlsanity.com/paper/2503.12406/) (2025)
- [Self-Motivated Growing Neural Network for Adaptive Architecture via Local Structural Plasticity](https://mlsanity.com/paper/2512.12713/) (2025)
- [Neuron-centric Hebbian Learning](https://mlsanity.com/paper/2403.12076/) (2024)
- [Evolutionary Developmental Biology Can Serve as the Conceptual Foundation for a New Design Paradigm in Artificial Intelligence](https://mlsanity.com/paper/2506.12891/) (2025)
- [Distilling a Modular Reservoir Through a Genomic Bottleneck](https://mlsanity.com/paper/2606.28380/) (2026)
- [Architecture Generalization with MetaNCA](https://mlsanity.com/paper/2607.07743/) (2026)

## Abstract (arXiv)

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, deep learning often requires considerable engineering effort to design high-performing neural architectures. By contrast, biological nervous systems are grown through a dynamic self-organizing process. In this paper, we take initial steps toward neural networks that grow through a developmental process that mirrors key properties of embryonic development in biological organisms. The growth process is guided by another neural network, which we call a Neural Developmental Program (NDP) and which operates through local communication alone. We investigate the role of neural growth on different machine learning benchmarks and different optimization methods (evolutionary training, online RL, offline RL, and supervised learning). Additionally, we highlight future research directions and opportunities enabled by having self-organization driving the growth of neural networks.