An artificial immune system is a class of computational methods inspired by the learning, memory, detection, and response mechanisms of biological immune systems. These systems are used for problem-solving tasks such as anomaly detection, optimization, classification, and adaptive security.
A class of computationally intelligent, rule-based machine learning systems inspired by the principles and processes of the vertebrate immune system. The algorithms are typically modeled after the immune system's characteristics of learning and memory for use in problem-solving.