Major knowledge –representation paradigms
In most early AI systems, knowledge representation was not explicitly recognized as an important issue in its own right, although most systems incorporated knowledge indirectly through rules and data structures. Some early researchers did address representation issues more directly. For example, the SIR reasoning system used Lisp property lists to represent and make inferences about information acquired from users; the Deacon system used ring structures to encode many kinds of knowledge. Including time-variant information; and F, Black stressed the need to make (and control) inferences about stored knowledge.