Logics for Knowledge-Based Systems: MLPM and MCL

Abstract

Several formal or executable specification languages have been developed for describing knowledge-based systems. Most of them are based on the KADS model of expertise or define their conceptual model as a modification of this model. Surveys of these languages can be found in [Treur & Wetter, 1993], [Fensel & van Harmelen, 1994], and [Fensel, 1995c]. Common to all formal specification approaches for knowledge-based systems is that a formal semantics has to cover three aspects: the specification of static aspects of a knowledge-based system, the specification of the dynamics of a knowledge-based system (i.e., its reasoning), and the combination of both, i.e. its overall semantics. For our study we restrict our attention to the second and third parts, because we think that the main improvements are necessary in the dynamic part. This part also introduces the main distinction between these approaches and many specification languages of software engineering which aim only at a purely functional description of a software system. In addition to a precise functional specification (i.e., the definitions of the goals that should be achieved by the knowledge-based system) specifications of knowledge-based systems have to cover the reasoning process and its use of knowledge, which enable reasonable problem-solving for the expected cases. An important part of the knowledge that must be specified is therefore knowledge about the way to achieve a solution and not just declarative knowledge about what a solution should be.