Types of computational self-awareness and how we might implement them

Computing systems increasingly comprise large numbers of heterogeneous subsystems, each with their own local perspective and goals, connected in dynamic networks, and interacting with each other and humans in ways which are difficult to predict. Nevertheless, users engaging with different parts of the system still expect high performance, reliability, security and other qualities, provided in a way that is robust or adaptive in the presence of unforeseen changes (including to users, the network, physical environment or the system itself). Examples of systems which are facing this challenge are wide-ranging and include robot swarms, personal devices, web services and sensor networks. In all these cases, advanced levels of autonomous behaviour can enable the system to adapt itself at run time, by learning behaviours in real time, appropriate to changing conditions.