The field of biologically inspired computing has generated many novel, interesting and useful computational systems. None of these systems alone is capable of approaching the level of behaviour for which the artificial intelligence and robotics communities strive. We suggest that it is now time to move on to integrating a number of these approaches in a biologically justifiable way. To this end we present a conceptual framework that integrates artificial neural networks, artificial immune systems and a novel artificial endocrine system. The natural counterparts of these three components are usually assumed to be the principal actors in maintaining homeostasis within biological systems. This chapter proposes a system that promises to capitalise on the self-organising properties of these artificial systems to yield artificially homeostatic systems. The components develop in a common environment and interact in ways that draw heavily on their biological counterparts for inspiration. A case study is presented, in which aspects of the nervous and endocrine systems are exploited to create a simple robot controller. Mechanisms for the moderation of system growth using an artificial immune system are also presented.