Pseudo-contractions as Gentle Repairs

Updating a knowledge base to remove an unwanted consequence is a challenging task. Some of the original sentences must be either deleted or weakened in such a way that the sentence to be removed is no longer entailed by the resulting set. On the other hand, it is desirable that the existing knowledge be preserved as much as possible, minimising the loss of information. Several approaches to this problem can be found in the literature. In particular, when the knowledge is represented by an ontology, two different families of frameworks have been developed in the literature in the past decades with numerous ideas in common but with little interaction between the communities: applications of AGM-like Belief Change and justification-based Ontology Repair. In this paper, we investigate the relationship between pseudo-contraction operations and gentle repairs. Both aim to avoid the complete deletion of sentences when replacing them with weaker versions is enough to prevent the entailment of the unwanted formula. We show the correspondence between concepts on both sides and investigate under which conditions they are equivalent. Furthermore, we propose a unified notation for the two approaches, which might contribute to the integration of the two areas

The model-based construction of a case-oriented expert system

Second generation expert systems should be based upon an expert\u27s high level understanding of the application domain and upon specific real world experiences. By having an expert categorize different types of relevant experiences and their components, hierarchies of abstract problems and operator classes are determined on the basis of the expert\u27s accumulated problem solving experiences. The expert\u27s global understanding of the domain is integrated with the experiences by a model of expertise. This model postulates problem classes at different levels of abstractions and associated skeletal plans. During a consultation with the expert system previously unseen types of input may be used to delineate a new problem. The application of the expert system can thus be situated in changing environments and contexts. With increasing dissimilarity between the cases that were analyzed during knowledge acquisition and the specific problem that is processed at the time of the application of the system, its performance gracefully degrades by supplying a more and more abstract skeletal plan. More specifically, the search space which is represented by the skeletal plan increases until the competence of the system is exceeded. This paper describes how such a case-oriented expert system is developed for production planning in mechanical engineering

Intelligent documentation as a catalyst for developing cooperative knowledge-based systems

In the long run, the development of cooperative knowledge-based systems for complex real world domains such as production planning in mechanical engineering should yield significant economic returns. However, large investments have already been made into the conventional technology. Intelligent documentation, which abstracts the current practice of the industry, is suggested as a stepping stone for developing such knowledge-based systems. A set of coordinated knowledge acquisition tools has been developed by which intelligent documents are constructed as an intermediate product, which by itself is already useful. Within the frame of the conventional technology, the task- and domain specific hypertext structures allow the reuse of production plans while simultaneously starting the development process for knowledge based systems

The model-based construction of a case-oriented expert system

Second generation expert systems should be based upon an expert's high level understanding of the application domain and upon specific real world experiences. By having an expert categorize different types of relevant experiences and their components, hierarchies of abstract problems and operator classes are determined on the basis of the expert's accumulated problem solving experiences. The expert's global understanding of the domain is integrated with the experiences by a model of expertise. This model postulates problem classes at different levels of abstractions and associated skeletal plans. During a consultation with the expert system previously unseen types of input may be used to delineate a new problem. The application of the expert system can thus be situated in changing environments and contexts. With increasing dissimilarity between the cases that were analyzed during knowledge acquisition and the specific problem that is processed at the time of the application of the system, its performance gracefully degrades by supplying a more and more abstract skeletal plan. More specifically, the search space which is represented by the skeletal plan increases until the competence of the system is exceeded. This paper describes how such a case-oriented expert system is developed for production planning in mechanical engineering

Meta-ontology fault detection

Ontology engineering is the field, within knowledge representation, concerned with using logic-based formalisms to represent knowledge, typically moderately sized knowledge bases called ontologies. How to best develop, use and maintain these ontologies has produced relatively large bodies of both formal, theoretical and methodological research. One subfield of ontology engineering is ontology debugging, and is concerned with preventing, detecting and repairing errors (or more generally pitfalls, bad practices or faults) in ontologies. Due to the logical nature of ontologies and, in particular, entailment, these faults are often both hard to prevent and detect and have far reaching consequences. This makes ontology debugging one of the principal challenges to more widespread adoption of ontologies in applications. Moreover, another important subfield in ontology engineering is that of ontology alignment: combining multiple ontologies to produce more powerful results than the simple sum of the parts. Ontology alignment further increases the issues, difficulties and challenges of ontology debugging by introducing, propagating and exacerbating faults in ontologies. A relevant aspect of the field of ontology debugging is that, due to the challenges and difficulties, research within it is usually notably constrained in its scope, focusing on particular aspects of the problem or on the application to only certain subdomains or under specific methodologies. Similarly, the approaches are often ad hoc and only related to other approaches at a conceptual level. There are no well established and widely used formalisms, definitions or benchmarks that form a foundation of the field of ontology debugging. In this thesis, I tackle the problem of ontology debugging from a more abstract than usual point of view, looking at existing literature in the field and attempting to extract common ideas and specially focussing on formulating them in a common language and under a common approach. Meta-ontology fault detection is a framework for detecting faults in ontologies that utilizes semantic fault patterns to express schematic entailments that typically indicate faults in a systematic way. The formalism that I developed to represent these patterns is called existential second-order query logic (abbreviated as ESQ logic). I further reformulated a large proportion of the ideas present in some of the existing research pieces into this framework and as patterns in ESQ logic, providing a pattern catalogue. Most of the work during my PhD has been spent in designing and implementing an algorithm to effectively automatically detect arbitrary ESQ patterns in arbitrary ontologies. The result is what we call minimal commitment resolution for ESQ logic, an extension of first-order resolution, drawing on important ideas from higher-order unification and implementing a novel approach to unification problems using dependency graphs. I have proven important theoretical properties about this algorithm such as its soundness, its termination (in a certain sense and under certain conditions) and its fairness or completeness in the enumeration of infinite spaces of solutions. Moreover, I have produced an implementation of minimal commitment resolution for ESQ logic in Haskell that has passed all unit tests and produces non-trivial results on small examples. However, attempts to apply this algorithm to examples of a more realistic size have proven unsuccessful, with computation times that exceed our tolerance levels. In this thesis, I have provided both details of the challenges faced in this regard, as well as other successful forms of qualitative evaluation of the meta-ontology fault detection approach, and discussions about both what I believe are the main causes of the computational feasibility problems, ideas on how to overcome them, and also ideas on other directions of future work that could use the results in the thesis to contribute to the production of foundational formalisms, ideas and approaches to ontology debugging that can properly combine existing constrained research. It is unclear to me whether minimal commitment resolution for ESQ logic can, in its current shape, be implemented efficiently or not, but I believe that, at the very least, the theoretical and conceptual underpinnings that I have presented in this thesis will be useful to produce more foundational results in the field

Explaining Postwar Strategic Cooperation between the United States and Its Former Adversaries

I present a bargaining theory of strategic cooperation--which I define as voluntary, deep, and enduring cooperation--that focuses on the influence of credible commitment problems to explain variation in the qualities of strategic cooperation. I argue that variations in a relationship's qualities of cooperation are primarily explained by credible commitment problems at the international and domestic levels. I identify three sources of credible commitment problems at the international level (spoiler problems, competitor problems, and other international conditions) and five sources of credible commitment problems at the domestic level (disinterest, trust, reconciliation, state capacity, and political unification problems) that might undermine a relationship's qualities of cooperation. I test my theory against a restricted universe of cases that is comprised of the U.S. wars from World War II to present, arguing that the two most likely sources of domestic credible commitment problems in these U.S. postwar contexts are reconciliation problems and political unification problems within the former U.S. adversary. My case analyses largely support my theory. This has substantial policy implications. My theory should now be tested on a broader array of strategic cooperation contexts to improve its generalizability.Doctor of Philosoph

Quantitative Variants of Language Equations and their Applications to Description Logics

Unification in description logics (DLs) has been introduced as a novel inference service that can be used to detect redundancies in ontologies, by finding different concepts that may potentially stand for the same intuitive notion. Together with the special case of matching, they were first investigated in detail for the DL FL0, where these problems can be reduced to solving certain language equations. In this thesis, we extend this service in two directions. In order to increase the recall of this method for finding redundancies, we introduce and investigate the notion of approximate unification, which basically finds pairs of concepts that “almost” unify, in order to account for potential small modelling errors. The meaning of “almost” is formalized using distance measures between concepts. We show that approximate unification in FL0 can be reduced to approximately solving language equations, and devise algorithms for solving the latter problem for particular distance measures. Furthermore, we make a first step towards integrating background knowledge, formulated in so-called TBoxes, by investigating the special case of matching in the presence of TBoxes of different forms. We acquire a tight complexity bound for the general case, while we prove that the problem becomes easier in a restricted setting. To achieve these bounds, we take advantage of an equivalence characterization of FL0 concepts that is based on formal languages. In addition, we incorporate TBoxes in computing concept distances. Even though our results on the approximate setting cannot deal with TBoxes yet, we prepare the framework that future research can build on. Before we journey to the technical details of the above investigations, we showcase our program in the simpler setting of the equational theory ACUI, where we are able to also combine the two extensions. In the course of studying the above problems, we make heavy use of automata theory, where we also derive novel results that could be of independent interest