An artificial endocrine-emotion model based on fuzzy logic

Abstract

For the past few years, the research of intelligence model based on biologicalinformation processing mechanisms has become an important area of artificial intelligence. The biological information processing system is mainly composed of nervous system, immune system and endocrine system. There is not only large loop among them, but also direct reciprocity, which plays an important role in the growing development and metabolism of organisms and maintains their vital movement together. As an important part of information processing system in living organisms, the endocrine system contains very complex and particular information processing mechanisms, including hormonal regulation mechanism, information delivery mechanism and emotion reacting mechanism. Extracting these mechanisms which are peculiar to endocrine system and establishing corresponding models and algorithms has important research value, which has been a hot issue in the research field of artificial intelligence. Shibata presented a hormone-like mechanism with an emphasis on human-robot interaction. Shen proposed a bio-inspired control method called Digital Hormone Model (DHM) to control the tasking and executing of robot swarms based on local communication,signal propagation, and stochastic reactions. Neal and Timmis put forward artificial endocrine system (AES) for the first time in 2003. They proposed an artificial homeostasis system later. Motivated by the high-level regulation mechanism of endocrine system, an agent self-organization algorithm of behavior was put forward. A hormone based tracking strategy for mobile target tracking in wireless sensor networks was presented. © 2012 Springer-Verlag London Limited.