# SAIS: A Novel Bio-Inspired Artificial Immune System Based on Symbiotic Paradigm

arXiv: https://arxiv.org/abs/2402.07244 · HTML: https://mlsanity.com/paper/2402.07244/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 25 references that are in the map.
- First posted on arXiv 11 Feb 2024.

## Builds on (most cited first, 3 of 3)

- [A Systematic Comparison Study on Hyperparameter Optimisation of Graph Neural Networks for Molecular Property Prediction](https://mlsanity.com/paper/2102.04283/) (2021)
- [A Novel Genetic Algorithm with Hierarchical Evaluation Strategy for Hyperparameter Optimisation of Graph Neural Networks](https://mlsanity.com/paper/2101.09300/) (2021)
- [A Genetic Algorithm with Tree-structured Mutation for Hyperparameter Optimisation of Graph Neural Networks](https://mlsanity.com/paper/2102.11995/) (2021)

## Built on by (most cited first, 1 of 1)

- [Position: Quantum Program Generation Must Prioritize Validity Over Probabilistic Scaling](https://mlsanity.com/paper/2607.15313/) (2026)

## Abstract (arXiv)

We propose a novel type of Artificial Immune System (AIS): Symbiotic Artificial Immune Systems (SAIS), drawing inspiration from symbiotic relationships in biology. SAIS parallels the three key stages (i.e., mutualism, commensalism and parasitism) of population updating from the Symbiotic Organisms Search (SOS) algorithm. This parallel approach effectively addresses the challenges of large population size and enhances population diversity in AIS, which traditional AIS and SOS struggle to resolve efficiently. We conducted a series of experiments, which demonstrated that our SAIS achieved comparable performance to the state-of-the-art approach SOS and outperformed other popular AIS approaches and evolutionary algorithms across 26 benchmark problems. Furthermore, we investigated the problem of parameter selection and found that SAIS performs better in handling larger population sizes while requiring fewer generations. Finally, we believe SAIS, as a novel bio-inspired and immune-inspired algorithm, paves the way for innovation in bio-inspired computing with the symbiotic paradigm.