An empirical analysis of terminological representation systems

The family of terminological representation systems has its roots in the representation system KL-ONE. Since the development of this system more than a dozen similar representation systems have been developed by various research groups. These systems vary along a number of dimensions.In this paper, we present the results of an empirical analysis of six such systems. Surprisingly, the systems turned out to be quite diverse leading to problems when transporting knowledge bases from one system to another. Additionally, the runtime performance between different systems and knowledge bases varied more than we expected. Finally, our empirical runtime performance results give an idea of what runtime performance to expect from such representation systems. These findings complement previously reported analytical results about the computational complexity of reasoning in such systems

Message-Passing Protocols for Real-World Parsing -- An Object-Oriented Model and its Preliminary Evaluation

We argue for a performance-based design of natural language grammars and their associated parsers in order to meet the constraints imposed by real-world NLP. Our approach incorporates declarative and procedural knowledge about language and language use within an object-oriented specification framework. We discuss several message-passing protocols for parsing and provide reasons for sacrificing completeness of the parse in favor of efficiency based on a preliminary empirical evaluation.Comment: 12 pages, uses epsfig.st

Terminological reasoning with constraint handling rules

Constraint handling rules (CHRs) are a flexible means to implement \u27user-defined\u27 constraints on top of existing host languages (like Prolog and Lisp). Recently, M. Schmidt-Schauß and G. Smolka proposed a new methodology for constructing sound and complete inference algorithms for terminological knowledge representation formalisms in the tradition of KLONE. We propose CHRs as a flexible implementation language for the consistency test of assertions, which is the basis for all terminological reasoning services. The implementation results in a natural combination of three layers: (i) a constraint layer that reasons in well- understood domains such as rationals or finite domains, (ii) a terminological layer providing a tailored, validated vocabulary on which (iii) the application layer can rely. The flexibility of the approach will be illustrated by extending the formalism, its implementation and an application example (solving configuration problems) with attributes, a new quantifier and concrete domains

Decidable Reasoning in Terminological Knowledge Representation Systems

Terminological knowledge representation systems (TKRSs) are tools for designing and using knowledge bases that make use of terminological languages (or concept languages). We analyze from a theoretical point of view a TKRS whose capabilities go beyond the ones of presently available TKRSs. The new features studied, often required in practical applications, can be summarized in three main points. First, we consider a highly expressive terminological language, called ALCNR, including general complements of concepts, number restrictions and role conjunction. Second, we allow to express inclusion statements between general concepts, and terminological cycles as a particular case. Third, we prove the decidability of a number of desirable TKRS-deduction services (like satisfiability, subsumption and instance checking) through a sound, complete and terminating calculus for reasoning in ALCNR-knowledge bases. Our calculus extends the general technique of constraint systems. As a byproduct of the proof, we get also the result that inclusion statements in ALCNR can be simulated by terminological cycles, if descriptive semantics is adopted.Comment: See http://www.jair.org/ for any accompanying file

Combining terminological and rule-based reasoning for abstraction processes

Terminological reasoning systems directly support the abstraction mechanisms generalization and classification. But they do not bother about aggregation and have some problems with reasoning demands such as concrete domains, sequences of finite but unbounded size and derived attributes. The paper demonstrates the relevance of these issues in an analysis of a mechanical engineering application and suggests an integration of a forward-chaining rule system with a terminological logic as a solution to these problems

A cognitive analysis of event structure

Events occupy a central place in natural language. Accordingly, an understanding of them is crucial if one is to have any kind of a theoretically well-motivated account of natural language understanding and generation. It is proposed here that speakers create a cognitive structure for each discourse and process it as they introduce sentences into the discourse. The structure for each sentence depends systematically on its tense, aspect and the situation type; its effect on the discourse also depends on the structures of the sentences that precede it. It is also argued that the perfective aspect introduces the structure of the given event in its entirety. The progressive, by contrast, introduces only the core of the structure of the given event excluding, in particular, its preparatory processes and resultant state. Similarly, the perfect and the perfective can be distinguished on the basis of the temporal schemata they introduce. While the perfective presents the event as complete, the perfect presents it as complete and closed; i.e., the perfect prevents succeeding discourse from being interpreted as falling during the given event. This is surprising since the perfect is otherwise simply the combination of the perfective and a tense. This paper also provides a key motivation for distinguishing between the preparatory processes and the preliminary stages of an event. This observation, which is crucial in distinguishing between the perfective and the progressive has not been made in the literature

Plan modifications versus plan generation : a complexity-theoretic perspective

The ability of a planner to modify a plan is considered as a valuable tool for improving efficiency of planning by avoiding the repetition of the same planning effort. From a computational complexity point of view, however, it is by no means obvious that modifying a plan is computationally as easy as planning from scratch if the modification has to follow the principle of "conservatism", i.e., to reuse as much of the old plan as possible. Indeed, considering propositional STRIPS planning, it turns out that conservative plan modification is as hard as planning and can sometimes be harder than plan generation. Furthermore, this holds even if we consider modification problems where the old and the new goal specification are similar. We put these results into perspective and discuss the relationship to existing plan modification systems. Although sometimes claimed otherwise, these systems do not address the modification problem, but use a non-conservative form of plan modification as a heuristic technique

PHI : a logic-based tool for intelligent help systems

We introduce a system which improves the performance of intelligent help systems by supplying them with plan generation and plan recognition components. Both components work in close mutual cooperation. We demonstrate two modes of cross-talk between them, one where plan recognition is done on the basis of abstract plans provided by the planner and the other where optimal plans are generated based on recognition results. The examples which are presented are taken from an operating system domain, namely from the UNIX mail domain. Our system is completely logic-based. Relying on a common logical framework--the interval-based modal temporal logic LLP which we have developed--both components are implemented as special purpose inference procedures. Plan generation from first and second principles is provided and carried out deductively, whereas plan recognition follows a new abductive approach for modal logics. The plan recognizer is additionally supplied with a probabilistic reasoner as a means to adjust the help provided for user-specific characteristics