Emergent coordination for distributed information management

With an increase in the complexity of information systems, decentralised management techniques are becoming important. Such information systems will generally involve various computational and data nodes, managed by various organisations with differing policies and needs. Furthermore, in the absence of a centralised manager, co-ordination and interaction policies between such nodes become crucial. Aspects of co-ordination can range from data formats describing shared information to convergence time to a desired goal. Each entity within such a networked environment operates with incomplete knowledge about the state of others, and makes use of an asynchronous mode of operation. An overview of techniques for supporting coordination in such an environment is first provided, followed by a proposed technique that makes use of Q-learning and data sharing between a collection of nodes, each of which is modelled as a neural network. We propose a decentralised technique for managing a cluster of nodes, where emergence is used to converge towards a `useful´ result