Loom or LOOM™ is a knowledge representation language developed by researchers in the Artificial Intelligence research group at the University of Southern California's Information Sciences Institute. The Loom project's goal is the development and fielding of advanced tools for knowledge representation and reasoning in Artificial Intelligence. Loom is a language and environment for constructing intelligent applications. At its heart is a knowledge representation system that is used to provide deductive support for the declarative portion of the Loom language. Declarative knowledge in Loom consists of definitions, rules, facts, and default rules. A deductive engine called a classifier utilizes forward-chaining, semantic unification and object-oriented truth maintenance technologies in order to compile the declarative knowledge into a network designed to efficiently support on-line deductive query processing. The Loom system implements a logic-based pattern matcher that drives a production rule facility and a pattern-directed method dispatching facility that supports the definition of object-oriented methods. The high degree of integration between Loom's declarative and procedural components permits programmers to utilize logic programming, production rule, and object-oriented programming paradigms in a single application. Loom can also be used as a deductive layer that overlays an ordinary CLOS (Common Lisp Object System) network. In this mode, users can obtain many of the benefits of using Loom without impacting the function or performance of their CLOS-based applications. Loom has recently been succeeded by PowerLoom
