Правило контрарного закрытия и полные расширения логического аппарата интеллектуальных систем с правилом входной резолюции

Решается проблема построения эффективных целеориентированных секвенциальных исчислений для классической логики первого порядка (без равенства). Приводятся результаты об их корректности и полноте. Устанавливается связь этих исчислений с неполной в общем случае входной резолюцией, заданной в виде так называемой SLD-резолюции для деревьев специального вида (SLD-деревьев). Эта связь дает простой способ построения полного в общем случае расширения SLD-резолюции за счет добавления к SLD-резолюции так называемого правила контрарного закрытия, которое может быть легко запрограммировано в интеллектуальных системах, использующих SLD-технику и требующих её полного расширения на случай формул произвольного вида. Библиогр.: 11 назв.Вирішується проблема побудови ефективних цілеорієнтованих секвенційних числень для класичної логіки першого порядку (без рівності). Наводяться результати їх коректності та повноти. Встановлюється зв’язок цих числень зі вхідною резолюцією (яка є неповною у загальному випадку), що задана у вигляді SLD-резолюції для дерев спеціального вигляду (SLD-дерев). Цей зв’язок надає простий спосіб побудови повного у загальному випадку розширення SLD-резолюції за рахунок додання до SLD-резолюції так званого правила контрарного закриття, яке може бути легко запрограмоване в інтелектуальні системи, що використовують SLD-техніку та потребують її повного розширення на випадок формул довільного вигляду. Бібліогр.: 11 назв.The problem of the construction of effective goal-oriented calculi for first-order classical logic (without equality) is solved. Some results on soundness and completeness of the calculi are given. Their connection with the input resolution that is incomplete in general and has the form of the SLD-resolution for special trees (the SLD-trees) is fixed. The connection gives a simple way for the construction of a complete extension of the SLD-resolution by means of adding a so-called contrary-closing rule, which easily can be implemented in intelligent systems using SLD-technique and requiring its complete extension for sets of arbitrary formulas. Refs.: 11 titles

Answer Set Planning Under Action Costs

Recently, planning based on answer set programming has been proposed as an approach towards realizing declarative planning systems. In this paper, we present the language Kc, which extends the declarative planning language K by action costs. Kc provides the notion of admissible and optimal plans, which are plans whose overall action costs are within a given limit resp. minimum over all plans (i.e., cheapest plans). As we demonstrate, this novel language allows for expressing some nontrivial planning tasks in a declarative way. Furthermore, it can be utilized for representing planning problems under other optimality criteria, such as computing ``shortest'' plans (with the least number of steps), and refinement combinations of cheapest and fastest plans. We study complexity aspects of the language Kc and provide a transformation to logic programs, such that planning problems are solved via answer set programming. Furthermore, we report experimental results on selected problems. Our experience is encouraging that answer set planning may be a valuable approach to expressive planning systems in which intricate planning problems can be naturally specified and solved

Extended Functional Unification ProGrammars

Functional Unification Grammars (PUGs) are popular for natural language applications because the formalism uses very few primitives and is uniform and expressive. In our work on text generation, we have found that it also has annoying limitations: it is not adapted to the expression of simple yet very common taxonomic relations and it does not allow easy manipulation of complex data-structures like lists or sets. We present in this paper a set of extensions that keep the desirable properties of the formalism but make it more flexible and easier to use. We first introduce the notion of typed features and typed constituents. Types define a structure over the set of primitive symbols used by the formalism. We then introduce extended unification: specialized unification methods can be defined for user-defined data-types. This extends the power of the system to handle complex data-structures efficiently. Taking advantage of a structured set of primitives and of specialized unification methods, the resulting formalism is more flexible, easier to use and produces better documented grammars than traditional functional unification. It can therefore be used to address deeper levels of text generation than was possible before

Programming constraint services

This thesis presents design, application, implementation, and evaluation of computation spaces as abstractions for programming constraint services at a high level. Spaces are seamlessly integrated into a concurrent programming language and make constraintbased computations compatible with concurrency through encapsulation. Spaces are applied to search and combinators as essential constraint services. State-of-the-art and new search engines such as visual interactive search and parallel search are covered. Search is expressive and concurrency-compatible by using copying rather than trailing. Search is space and time efficient by using recomputation. Composable combinators, also known as deep-guard combinators, stress the control facilities and concurrency integration of spaces. The implementation of spaces comes as an orthogonal extension to the implementation of the underlying programming language. The resulting implementation is shown to be competitive with existing constraint programming systems.Diese Dissertation beschreibt Entwurf, Verwendung, Implementierung und Evaluierung von Computation Spaces für die Programmierung von Constraintdiensten. Spaces werden in eine nebenläufige Programmiersprache integriert. Sie fungieren als Kapseln für Berechnungen mit Constraints. Dadurch wird die Kompatibilität zu nebenläufigen Berechnungen gewährleistet. Suche und Kombinatoren sind zentrale Constraintdienste, die mit Spaces programmiert werden. Es werden sowohl übliche, als auch vollkommen neue Suchmaschinen, wie zum Beispiel interaktive Suche und parallele Suche, vorgestellt. Durch Kopieren wird Suche ausdrucksstark und kompatibel mit Nebenläufigkeit. Durch Wiederberechnung wird Suche effizient hinsichtlich Speicherbedarf und Laufzeit. Kombinatoren, die ineinander geschachtelt werden können (so genannte deep-guard Kombinatoren), verdeutlichen die Kontrollmöglichkeiten von Spaces. Die Implementierung von Spaces erfolgt als orthogonale Erweiterung einer Implementierung für die zugrundeliegende Programmiersprache. Das Ergebnis ist konkurrenzfähig zu existierenden Constraintprogrammiersystemen