An immune algorithm for multiagent: application to adaptive noise neutralization

A new information processing architecture is extracted from the immune system. By focusing on informational features of the immune system (i.e. specificity, diversity, tolerance, and memory), an immune algorithm is proposed. The algorithm proceeds in three steps: diversity generation, establishment of self-tolerance, and memorizing non-self. The algorithm may be used typically to model the system by distributed agents where the system (the self) as well as the environment (the non-self) are unknown or cannot be modeled. Agent-based architecture based on the local memory hypothesis and network-based architecture based on the network hypothesis are discussed. Agent-based architecture is elaborated with the application to an adaptive system where the knowledge about environment is not available. Adaptive noise neutralization is formalized and simulated for a simple plant.