Autonomic Computing

The approaches to implement intelligent systems can be classified into those of biological organisms, silicon automata, and computing systems. Based on CI studies, autonomic computing [Wang, 2004] is proposed as a new and advanced computing technique built upon the routine, algorithmic, and adaptive systems. The approaches to computing can be classified into two categories known as imperative and autonomic computing. Corresponding to these, computing systems may be implemented as imperative or autonomic computing systems.

Definition 8. An imperative computing system is a passive system that implements deterministic, context-free, and stored-program controlled behaviors.

Definition 9. An autonomic computing system is an intelligent system that autonomously carries out robotic and interactive actions based on goal- and event-driven mechanisms.

The imperative computing system is a traditional passive system that implements deterministic, context-free, and stored-program controlled behaviors, where a behavior is defined as a set of observable actions of a given computing system. The autonomic computing system is an active system that implements nondeterministic, context-dependent, and adaptive behaviors, which do not rely on instructive and procedural information, but are dependent on internal status and willingness that formed by long-term historical events and current rational or emotional goals.

The first three categories of computing techniques as shown in Table 3 are imperative. In contrast, the autonomic computing systems are an active system that implements nondeterministic, context-sensitive, and adaptive behaviors. Autonomic computing does not rely on imperative and procedural instructions, but are dependent on perceptions and inferences based on internal goals as revealed in CI.