Logical foundations for rule-based systems.
Rule-Based Systems (RBSs) constitute a powerful tool for specification of knowledge in design and implementation of knowledge-based systems in applied artificial intelligence and knowledge engineering. The aim of this book is to present RBSs from the logical perspective, in a relatively complete methodology. The author's concepts and his personal experience with RBSs support the original contents on the theoretical and practical approach to RBSs. The main topics exposed within this special monograph on RBSs are: logical foundations of RBSs (including knowledge representation and inference with proportional, attribute-based and first-order logic), knowledge representation, inference and inference control in RBSs (including extended forms of rules and specialized reference control mechanisms), definitions and verification of formal properties of RBSs assuring their correct work, and finally, RBS design issues (covering a systematic RBS design approach combined with on-line verification). The RBS analysis is presented at a conceptual level; the logical definitions are systematically introduced and supported by practical implementation-oriented solutions. In several cases, the discussion is continued into details of implementation, and illustrated by working solutions in PROLOG. The special feature of this book on RBSs is that, in contrast to the majority of textbooks on AI, KE and RBSs (which attempt to present a mixture of different approaches), the present RBS monograph follows a unitary line of formalism, namely the propositional calculus, defines and explains the technical issues in detail, and provides practical solutions illustrated with PROLOG code. The novelty of theoretical aspects on RBSs focuses on three issues: knowledge algebraizations, hierarchical organization of knowledge, and the formalization of design and verification. These issues are supported by the following original approaches: (a) Four types of logical languages are presented for encoding RBSs, with special attention paid to attribute-based languages. (b) The logical reference method called backward dual resolution is shown to be especially suitable for the analysis of completeness and reduction of RBS rules; it can be applied to first-order logic-based RBSs for providing satisfaction of rule preconditions in the case of complex DNF-like formulae. (c) The author proposes an extended, frame-like form of inference rules containing numerous components, allowing for dynamic memory modification, and encoding inference control in declarative rules. (d) The Extended Tabular Systems (XTT) knowledge representation method is used to link tabular knowledge components into a tree structure for efficient control, allowing also for non-atomic values of the attributes. (e) Logical definitions and a practical approach are introduced for the verification of certain important formal properties of RBSs. (f) A new design paradigm for RBSs is proposed, which incorporates graphical knowledge representation and on-line verification. (g) Finally, many theoretical ideas and practical aspects of RBSs are encoded in PROLOG as a meta-level code. The book is organized in five main parts, with 21 chapters and two appendices, as follows: Part I (Logical foundations of RBSs) contains Chapter 1 (Propositional logic), Chapter 2 (Predicate calculus), Chapter 3 (Attribute logic), Chapter 4 (Resolution), and Chapter 5 (Dual resolution). Part II (Principles of RBSs) encloses Chapter 6 (Basic structure of RBSs), Chapter 7 (RBSs in propositional logic), Chapter 8 (RBSs in attribute logic), Chapter 9 (RBSs in first-order logic), Chapter 10 (Inference control in RBSs), and Chapter 11 (Logic programming and Prolog). Part III (Verification of RBSs) gathers Chapter 12 (Principles of verification of RBSs), Chapter 13 (Analysis of redundancy), Chapter 14 (Analysis of indeterminism and inconsistency), Chapter 15 (Reduction of RBSs) and Chapter 16 (Analysis of completeness). Part IV (Design of RBSs) is the host for Chapter 17 (An introduction to design of RBSs), Chapter 18 (Logical foundations: the \(\Psi\)-trees based approach), Chapter 19 (Design of tabular RBSs with XTT), Chapter 20 (Design example: Thermostat), and Chapter 21 (Concluding remarks). The final Part V (Closing remarks and appendices) is a valuable survey of (re)sources on RBS information and reference: Appendix A (Selected RBSs and tools) and Appendix B (Selected web resources). The book is addressed to researchers, students and engineers interested in RBS technology under all aspects, from RBS theoretical foundations to RBS inference, design and verification, providing equally a source of inspiration for knowledge engineering theory and practice.
scientific article; zbMATH DE number 5015433