IIDLE: An Immunological Inspired Distributed Learning Environment for Multiple Objective and Hybrid Optimisation

The acquired immune system is a robust and powerful information processing system that demonstrates features such as decentralised control, parallel processing, adaptation, and learning. The immunological inspired distributed learning environment (IIDLE) is a clonal selection inspired artificial immune system (AIS) that exploits the inherent parallelism, decentralised control, spatially distributed nature, and learning behaviours of the immune system. The distributed architecture and modular process of the IIDLE framework are shown to be useful features on complex search and optimisation tasks in addition to facilitating some of the desired robustness of the inspiration.