QML-AiNet: An Immune-Inspired Network Approach to Qualitative Model Learning

In this paper we continue the research on applying immune-inspired algorithms as search strategies to Qualitative Model Learning (QML). A new search strategy based on opt-AiNet is proposed, and this results in the development of a novel QML system called QML-AiNet. The performance of QML-AiNet is compared with previous work using the CLONALG approach. Experimental results shows that although not as efficient as CLONALG, the opt-AiNet based approach still shows promising results for learning qualitative models. In addition, possible future work to further improve the efficiency of QML-AiNet is also pointed out.