MORPH: Self-Organising Multi-Robot Task Allocation via Neuroplasticity-Inspired Adaptive Topology

arXiv:2609.32745 · cs.RO · Submitted 2026-09-26 · Read on arXiv

cs.RO

Submitted: 2026-09-26

Updated: 2026-09-26

Code: https://github.com/Cyber-physical-Systems-Lab/morph_v2

Terminology

• Distribution Shift — 13× in this paper · explained in 5 episodes
• Pruning — 11× in this paper · explained in 4 episodes
• Adaptation — 9× in this paper · explained in 1 episode
• Ablation — 8× in this paper · explained in 1 episode
• Core — 7× in this paper · explained in 2 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• Reinforcement Learning — 5× in this paper · explained in 4 episodes
• Adaptability — 4× in this paper · explained in 1 episode
• Calibration — 3× in this paper · explained in 7 episodes
• Multi-Agent System — 3× in this paper · explained in 6 episodes
• Cooperation — 2× in this paper · explained in 2 episodes
• International Conference on Machine Learning — 2× in this paper
• Trace — 2× in this paper · explained in 2 episodes
• Active Visual Search — 1× in this paper · explained in 1 episode
• Adaptive Multi-Agent Systems — 1× in this paper
• Agent Memory — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Closest-Target Assignment — 1× in this paper
• Computational Biology — 1× in this paper · explained in 2 episodes
• Convergence Guarantees — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• International Conference on Learning Representations — 1× in this paper
• Meta-learning — 1× in this paper · explained in 2 episodes
• Proceedings of the American Control Conference — 1× in this paper
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Reward Shaping — 1× in this paper · explained in 2 episodes
• Task-Similarity Gate — 1× in this paper

Sources

• Understanding plasticity in neural networks
• Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity
• Differentiable plasticity: training plastic neural networks with backpropagation
• CaMKII activation supports reward-based neural network optimization through Hamiltonian sampling

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