Problem-solving methods provide reusable architectures and components for implementing the reasoning part of knowledge-based systems.

The software and knowledge engineering literature defines maintenance strategies for seven main types of knowledge: words; sentences; behavioural knowledge; and meta-knowledge. Meta-knowledge divides into problem solving methods; quality knowledge; fix knowledge; social knowl- 5 edge; and processing activities. There are five main ways in which these seven knowledge types are processed: acquire; operationalise; fault; fix; and preserve. We review systems that contribute to these 7 5 = 35 types of knowledge maintenance. 1 Introduction 10 A general trend in the twentieth century is an increasing level of doubt about the things we speak or write or try to enter into programs. Popper argues that all knowledge is an hypothesis since nothing can ever be ultimately proved; Submitted to the Knowledge Engineering Review page 2 of 73 our currently believed ideas are merely those that have survive active attempts to refute them [89]. Knowledge representation theorists stress that KBs are...

. The paper introduces an approach for the specification and verification of knowledge-based systems combining conceptual and formal techniques. We identify four elements of the specification of a knowledge-based system: a task definition, a problem-solving method, a domain model, and an adapter that relates the other elements. We present abstract data types and a variant of dynamic logic as formal means to specify and verify these different elements. As a consequence of our conceptual model we can decompose the overall verification task of the knowledge-based systems into different proof obligations. Each proof obligation deals with a different aspect of the entire system. The use of the conceptual model in specification and verification improves understandability and reduces the effort for both activities. The modularization enables reuse of specifications and proofs. A knowledge-based system can be build by combing and adapting different components. 1 INTRODUCTION During the last ...

Reusable problem-solving methods as provided by the PROTÉGÉ-II improve knowledge engineering by allowing developers to design reasoners quickly from pre-existing components. The PROTÉGÉ-II approach allows developers to select methods from a library, and to map the methods to a domain ontology. Still, these methods lack a clear conceptual and formal description that would enable their reuse through matching their competence and assumptions with the available domain knowledge and the given task. KARL is a conceptual and formal knowledge-specification language that provides modeling primitives for specifying problem-solving methods. In this paper, we show how the code and informal descriptions of problem-solving methods in PROTÉGÉ-II can be complemented with the conceptual and formal method definitions in KARL. For our case study we choose two methods from the PROTÉGÉ-II framework: chronological backtracking and a task-specific refinement, the board-game method. In addition to the concept...

. We discuss the use of the Karlsruhe Interactive Verifier (KIV) for the verification of conceptual and formal specifications of knowledge-based systems. KIV was originally developed for the verification of procedural programs but it fits well for verifying knowledge-based systems. Its specification language is based on algebraic specification means for the functional specification of components and dynamic logic for the algorithmic specification. It provides an interactive theorem prover integrated into a sophisticated tool environment supporting aspects like the automatic generation of proof obligations, generation of counter examples, proof management, proof reuse etc. Only through this support, verification of complex specifications becomes possible. We provide some examples on how to specify and verify tasks, problem-solving methods, and their relationships. Keywords. Knowledge-based systems, knowledge-level modelling, formal specification, verification, interactive th...

This paper is directed at two central objectives. The first is to identify and establish areas of overlap between the expert and database system domains. The second is to present a view of existing and ongoing work within the expert systems community concerning the Verification and Validation (V&V) of rule bases. This review is directed towards the database community with the express aim of identifying possibilities where expert system V&V knowhow may also be of value to the database community, especially with respect to the identified areas of overlap. 1. Introduction This paper seeks firstly to establish some common ground between the Validation and Verification (V&V) of databases and rules bases, and secondly to identify possible areas where rule base V&V techniques may be applicable with respect to database systems. There are, in the author's view, three main areas where the domains of databases and expert systems interconnect. The first is concerned with the generally acknowledge...

Situated cognition (SC) and knowledge maintenance are intimately connected. We say that SC motivates research into KM and KM assess SC. If knowledge is situated, then a symbolic KB will require modification as the situation changes. However, if we could demonstrate that the 5 process of change dictated by SC is tamed via current KM tools, then the case for concerning ourselves with SC becomes weak. We argue here that (i) there is enough evidence to support the view that SC is a very strong motivation for KM; but (ii) there is not enough evidence to support the view that KM has tamed the problem of SC. That is, the current gener- 10 ation of KM tools may be an inadequate response to the challenge of SC for symbolic knowledge based systems. 1 Introduction "What is wanted is not the will to believe, but the will to find out, which is the exact opposite." 15 -- Bertrand Russell "We should no longer ask if we should measure, the question today is how." -- Dieter Rombach 20 Proponents of...

This paper is directed at two central objectives. The first is to identify and establish areas of overlap between the expert and database system domains. The second is to present a view of existing and ongoing work concerning the Verification, Validation and Integrity (VV&I) of rule base and database systems. The paper combines reviews from the two perspectives of the expert systems and database systems communities, with the express aim of identifying possibilities where VV&I knowhow of the one may also be of value to the other (and viceversa) , especially with respect to the identified areas of overlap. 1 Introduction Validation, verification and integrity (VV&I) issues are of primary importance to both expert and database systems (ESs and DBSs), since they relate to the fundamental question, "does a system provide a useful solution to the problems it sets out to solve?". This paper examines these issues from two perspectives, i.e. expert systems and database systems. The aim is to i...

Situated cognition motivates a review of knowledge maintenance. If knowledge is situated, then a symbolic knowledge base will require modification as the situation changes. We examine the AI and software engineering literature which relates to acquiring and changing programs. Based 5 on a reverse engineering of that literature, we see that strategies have been offered to maintain different types of knowledge: words; sentences; behavioural knowledge; and meta-knowledge. Meta-knowledge divides into problem solving methods; quality knowledge; fix knowledge; social knowledge; and processing activities. We see several kinds of processing activities in 10 the literature: acquire; operationalise; fault; fix; and preserve. To date, no single strategy maintains all types of knowledge or performs all processing activities. However, we can say that many of these processing activities perform some kind of search space reflection. We can use this framework as follows. By using the quality knowled...

Artifical Intelligence (AI) is useful. AI can deliver more functionality for reduced cost. AI should be used more widely but won’t be unless developers can trust adapative, nondeterministic, or complex AI systems. Verification and validation is one method used by software analysts to gain that trust. AI systems have features that make them hard to check using conventional V&V methods. Nevertheless, as we show in this article, there are enough alternative readily-available methods that enable the V&V of AI software.