Continuous collaboration for changing environments

Abstract

Collective autonomic systems (CAS) are distributed collections of agents that collaborate to achieve the system’s goals but autonomously adapt their behavior. We present the teacher/student architecture for locally coordinated distributed learning and show that in certain scenarios the performance of a swarm using teacher/student learning can be significantly better than that of agents learning individually. Teacher/student learning serves as foundation for the continuous collaboration (CC) development approach. We introduce CC, relate it to the EDLC, a life cycle model for CAS, and show that CC embodies many of the principles proposed for developing CAS.