Antoni Ligęza

The HeKatE methodology. Hybrid engineering of intelligent systems

The HeKatE methodology. Hybrid engineering of intelligent systems This paper describes a new approach, the HeKatE methodology, to the design and development of complex rule-based systems for control and decision support. The main paradigm for rule representation, namely, eXtended Tabular Trees (XTT), ensures high density and transparency of visual knowledge representation. Contrary to traditional, flat rule-based systems, the XTT approach is focused on groups of similar rules rather than on single rules. Such groups form decision tables which are connected into a network for inference. Efficient inference is assured as only the rules necessary for achieving the goal, identified by the context of inference and partial order among tables, are fired. In the paper a new version of the language—XTT22—is presented. It is based on ALSV(FD) logic, also described in the paper. Another distinctive feature of the presented approach is a top-down design methodology based on successive refinement of the project. It starts with Attribute Relationship Diagram (ARD) development. Such a diagram represents relationships between system variables. Based on the ARD scheme, XTT tables and links between them are generated. The tables are filled with expert-provided constraints on values of the attributes. The code for rule representation is generated in a humanreadable representation called HMR and interpreted with a provided inference engine called HeaRT. A set of software tools supporting the visual design and development stages is described in brief.

A study of methodological issues in design and development of rule-based systems: proposal of a new approach

Rule‐based systems (RBSs) constitute a powerful technology for declarative encoding and automated processing of large bodies of knowledge. A typical RBS consists of a knowledge base containing facts and production rules, and an inference engine managing the reasoning process. Despite their simple conceptual scheme, design and development of a RBS often turn out to be unexpectedly complex task. This paper presents an overview of issues concerning design and development of such systems. Differences between RBSs and classical software are exemplified, and design and implementation issues are analyzed. A novel, consistent, three‐phase methodology incorporating conceptual, logical, and physical design is outlined. Moreover, tools supporting the complete design and development process are presented.

HalVA - rule analysis framework for XTT2 rules

Quality and reliability issues are important in development and exploration of rule-based systems. In the paper a formalized knowledge representation for rules called XTT2 is considered. It is a rule language based on an expressive attribute logic called ALSV(FD). A custom runtime and verification framework for XTT2 called HalVA is proposed. It allows for verification of certain formal properties of rules, including determinism, subsumption or completeness.

Algorithms for rule inference in modularized rule bases

In the paper an extended knowledge representation for rules is considered. It is called Extended Tabular Trees (XTT2) and it provides a network of decision units grouping rules working in the same context. The units are linked into an inference network, where a number of inference options are considered. The original contribution of the paper is the proposal and formalization of several different inference algorithms working on the same rule base. Such an approach allows for a more flexible rule design and deployment, since the same knowledge base may be used in different ways, depending on the application.

On the quality evaluation of scientific entities in Poland supported by consistency-driven pairwise comparisons method

Comparison, rating, and ranking of alternative solutions, in case of multicriteria evaluations, have been an eternal focus of operations research and optimization theory. There exist numerous approaches at practical solving the multicriteria ranking problem. The recent focus of interest in this domain was the event of parametric evaluation of research entities in Poland. The principal methodology was based on pairwise comparisons. For each single comparison, four criteria have been used. One of the controversial points of the assumed approach was that the weights of these criteria were arbitrary. The main focus of this study is to put forward a theoretically justified way of extracting weights from the opinions of domain experts. Theoretical bases for the whole procedure are based on a survey and its experimental results. Discussion and comparison of the two resulting sets of weights and the computed inconsistency indicator are discussed.

A New Approach to Multiple Fault Diagnosis: A Combination of Diagnostic Matrices, Graphs, Algebraic and Rule-Based Models. The Case of Two-Layer Models

A New Approach to Multiple Fault Diagnosis: A Combination of Diagnostic Matrices, Graphs, Algebraic and Rule-Based Models. The Case of Two-Layer Models The diagnosis of multiple faults is significantly more difficult than singular fault diagnosis. However, in realistic industrial systems the possibility of simultaneous occurrence of multiple faults must be taken into account. This paper investigates some of the limitations of the diagnostic model based on the simple binary diagnostic matrix in the case of multiple faults. Several possible interpretations of the diagnostic matrix with rule-based systems are provided and analyzed. A proposal of an extension of the basic, single-level model based on diagnostic matrices to a two-level one, founded on causal analysis and incorporating an OR and an AND matrix is put forward. An approach to the diagnosis of multiple faults based on inconsistency analysis is outlined, and a refinement procedure using a qualitative model of dependencies among system variables is sketched out.

Designing reliable web security systems using rule-based systems approach

This paper shows that rule-based web security systems, such as firewalls, can be largely improved by using formal design and verification techniques. The principal idea consists of an integrated design and verification methodology, supported by an integrated graphical environment for rule-based systems development. System structure is described in a XML-based meta-level knowledge representation language. System domain knowledge and semantics is represented in RDF and Ontologies-based description. Formal properties of the system can be verified on-line by an integrated Prolog-based inference engine.

Proposal of Formal Verification of Selected BPMN Models with Alvis Modeling Language

BPMN is a leading visual notation for modeling business processes. Although there is many tools that allows for modeling using BPMN, they mostly do not support formal verification of models. The Alvis language was developed for modeling and verification of embedded systems. However, it is suitable for the modeling of any information systems with parallel subsystems. The goal of this paper is to describe the concept of using Alvis for a formal verification of selected BPMNmodels. In the paper a translation from BPMN to Alvis model is proposed. The translation is discussed and evaluated using a simple yet illustrative example.

Proposal of Representing BPMN Diagrams with XTT2-Based Business Rules

Business Processes describe operations of an organization.However, they do not take into account such aspects as detailed logic specification or process implementation. Business Rules are generally better suited for these purposes. Although there is ongoing research on integration of Business Processes with Business Rules, there is no standardized methodology for this integration.We propose a new method of providing visual rule modeling for specification of Business Process logic. In the paper, an outline of the integration of BPMN Business Processes with XTT2 Business Rules is sketched. The method allows for translating selected BPMN models to the XTT2 Business Rules, and executing them using the HeaRT rule engine.

Overview of knowledge formalization with XTT2 rules

The paper discusses a new formalized knowledge representation for rule-based systems called XTT2. This hybrid knowledge representation combines decision diagrams with extended decision tables. A single decision table contains a set of rules of similar structure operating within a common context. The structure of XTT2 constitutes a hierarchical knowledge representation consisting of lower level knowledge components, where specification is provided by a set of rules working in the same context, and at the higher level, where the decision diagram defines the overall structure of the knowledge base. This model has a concise formalization which opens up possibility for rigorous design and verification. The focus of the paper is on the presentation of the formal aspects of the approach starting from an initial logical specification.