Формалізація базових алгоритмів співставлення зі зразком в продукційних системах

Currently, there are several models of formalization of production systems. The formalization in terms of the first-order logic is the most universal. However, such formalization is not provided for all inference machinery in production systems. In particular, among the basic pattern matching algorithms, the generalized formal description was proposed only for the Rete algorithm. In the paper, the formalized description of the production system and basic matching algorithms (Rete, Treat) for further resource intensity assessment at the design stage was presented in a single format. A formal presentation of the compilation and implementation of the data flow network of the Treat algorithm was proposed. Based on the proposed formalization, the memory consumption calculation model for the Treat algorithm was extended due to taking into account memory consumption to preserve the conflict set and agree variables in the terminal vertices of the data flow network. In the future, the proposed single format of the presentation of the basic algorithms can be used for the resource intensity assessment of the Treat algorithm based on the mathematical models proposed for the Rete algorithm.В статье в едином формате представлено формализованное описание продукционной системы, компиляция Rete- и Treat-сети потока данных, а также правил перехода между узлами Treat сети. Предложена формализация Treat алгоритма сопоставления, которая может быть использована для дальнейшей оценки средней сложности. Расширена модель расчета затрат памяти для Treat алгоритма.В статті в єдиному форматі представлено формалізований опис продукційної системи, компіляцію Rete та Treat мережі потоку даних, а також правил переходу між вузлами Treat мережі. Запропоновано формалізацію співставлення за Treat алгоритмом, яка може бути використана для подальшої оцінки складності. Розширено модель розрахунку витрат пам’яті для Treat алгоритму

PERFORMANCE EVALUATION OF THE INFERENCE STRUCTURE IN EXPERT SYSTEM ABSTRACT

There are a variety of factors that affect the performance of an expert system. This paper presents an evaluating method focusing on the complexity, costs and efficiency of inference structure in a rule / Knowledge-source based expert system. The performance measuring factors proposed here, when fedback to Knowledge engineers, can help them gain a quantitative understanding of reasoning performance of Knowledge acquired at the (early) stages of the development life cycle, and enable them to make a numeric comparison and a choice among several structures, or have some refinements. This paper also presents some application examples of this evaluating method and describes an evaluating facility based on it.