Description logic (DL) ABoxes are a tool for describing the state of affairs in an application domain. In this paper, we consider the problem of updating ABoxes when the state changes. We assume that changes are described at an atomic level, i.e., in terms of possibly negated ABox assertions that involve only atomic concepts and roles. We analyze such basic ABox updates in several standard DLs by investigating whether the updated ABox can be expressed in these DLs and, if so, whether it is computable and what is its size. It turns out that DLs have to include nominals and the “@” constructor of hybrid logic (or, equivalently, admit Boolean ABoxes) for updated ABoxes to be expressible. We devise algorithms to compute updated ABoxes in several expressive DLs and show that an exponential blowup in the size of the whole input (original ABox + update information) cannot be avoided unless every PTIME problem is LOGTIMEparallelizable. We also exhibit ways to avoid an exponential blowup in the size of the original ABox, which is usually large compared to the update information.

In previous work we advocated continued development of specifications in the presence of inconsistency. To support this we presented quasi-classical (QC) logic for reasoning with inconsistent specifications. The logic allows the derivation of non-trivial classical inferences from inconsistent information. In this paper we present a development called labelled QC logic, and some associated analysis tools, that allows the tracking and diagnosis of inconsistent information. The results of analysis are then used to guide further development in the presence of inconsistency. We illustrate the logic and our tools by specifying and analysing parts of the London Ambulance Service. We argue that the scalability of our approach is made possible by deploying the ViewPoints framework for multi-perspective development, such that our analysis tools are only used on partial specifications of a manageable size. 1. Motivation and Background Inconsistent specifications are an inevitable intermediate p...

In this paper we address a specific computational aspect of belief revision: The size of the propositional formula obtained by means of the revision of a formula with a new one. In particular, we focus on the size of the smallest formula equivalent to the revised knowledge base. The main result of this paper is that not all formalizations of belief revision are equal from this point of view. For some of them we show that the revised knowledge base can be expressed with a formula admitting a polynomial-space representation (we call these results "compactability" results). On the other hand we are able to prove that for other ones the revised knowledge base does not always admit a polynomial-space representation, unless the polynomial hierarchy collapses at a sufficiently low level ("non-compactability" results). The time complexity of query answering for the revised knowledge base has definitely an impact on being able to represent the result of the revision compactly. Nevertheless form...

If a new piece of information contradicts our previously held beliefs, we have to revise our beliefs. This problem of belief revision arises in a number of areas in Computer Science and Artificial Intelligence, e.g., in updating logical database, in hypothetical reasoning, and in machine learning. Most of the research in this area is influenced by work in philosophical logic, in particular by Gardenfors and his colleagues, who developed the theory of belief revision. Here we will focus on the computational aspects of this theory, surveying results that address the issue of the computational complexity of belief revision.

Practical workflow systems need to be able to tolerate deviations from the initial process model because of un-anticipated situations. They should also be able to accommodate deviations in the format of the forms and data being manipulated. We offer a framework for treating both kinds of deviations uniformly, by applying ideas from programming languages (with workflow agents as potential on-line exception handlers) to workows that have been reified as objects in classes with special attributes. As a result, only a small number of new constructs, which can be applied orthogonally, need to be introduced. Special run-time checks are used to deal with the consequences of permitting deviations from the norm to persist as violations of constraints.

Extending database-like techniques to semi-structured and Web data sources is becoming a prominent research field. These data sources are essentially collections of textual documents. Hence, in this context, one of the key tasks consists in wrapping documents to build database abstractions of their content that can be manipulated using high-level tools. However, the degree of heterogeneity and the lack of structure make standard grammar parsers excessively rigid, and often unable to capture the richness of constructs in these documents. This paper presents Minerva, a formalism for writing wrappers around Web sites and other textual data sources. The key feature of Minerva is the attempt to couple the benefits of a declarative, grammar-based approach, with the flexibility of procedural programming. This is done by enriching regular grammars with an explicit exception-handling mechanism. Contributions of the paper stand in the definition of the formalism, and in the description of its i...

A vast and interesting family of natural semantics for belief revision is defined. Suppose one is given a distance d between any two models. One may then define the revision of a theory K by a formula ff as the theory defined by the set of all those models of ff that are closest, by d, to the set of models of K. This family is characterized by a set of rationality postulates that extends the AGM postulates. The new postulates describe properties of iterated revisions. 1 Introduction 1.1 Overview and related work The aim of this paper is to investigate semantics and logical properties of theory revisions based on an underlying notion of distance between individual models. In many situations it is indeed reasonable to assume that the agent has some natural way to evaluate the distance between any two models of the logical language of interest. The distance between model m and model m 0 is a measure of how far m 0 appears to be from the point of view of m. This distance may me...

The thesis proposes a number of techniques for elaborating requirements constructively from high-level goals. The techniques are based on the KAOS goal-oriented method for requirements engineering. This method consists in identifying goals and refining them into subgoals until the latter can be assigned as responsibilities of single agents such as humans, devices and software. Domain properties and assumptions about the software environment are also used during the goal refinement process. The method supports the exploration of alternative goal refinements and alternative responsibility assignments of goals to agents. It also supports the identification and resolution of conflicts between goals, and the identification and resolution of exceptional agent behaviors, called obstacles, that violate goals and assumptions produced during the goal refinement process. The thesis enriches the KAOS framework through three kinds of techniques: (a) techniques for identifying agents, goal refinements, and alternative responsibility assignments, and for deriving agent interfaces from such responsibility assignments; (b) techniques for deriving operational requirements from goal specifications; (c) techniques for generating obstacles to the satisfaction of idealized goals and assumptions, and for generating alternative obstacle resolutions. The result is a coherent body of systematic techniques for requirements elaboration that are both theoretically well-founded (a formal model of agent is defined) and effective in practice (the techniques are validated on two real case studies of significant size: the London ambulance despatching system, and the Bay Area Rapid Transit train system).

The ability of Database Systems to cope with changing situations and information coming from different sources is crucial for their applicability in real-world scenarios. Recent work in the field of belief revision and update has provided us techniques to handle change. In this paper we introduce a different form of revision aiming at capturing the process of "merging" possibly inconsistent pieces of information. We call this process arbitration. Along the lines of Gardenfors' work, we propose a set of postulates for this operator and prove a representation theorem. Keywords: knowledge representation, belief revision, non-monotonic reasoning. 1 Introduction One of the main challenges of today's software and databases systems is their ability to manage a large amount of information coming from different sources and at different moments in time. Advanced databases systems must cope with a changing world and not completely reliable sources of information by adopting a "principled" strat...

Approximating a general formula from above and below by Horn formulas (its Horn envelope and Horn core, respectively) was proposed in [22] as a form of "knowledge compilation, " supporting rapid approximate reasoning; on the negative side, this scheme is static in that it supports no updates, and has certain complexity drawbacks pointed out in [17]. On the other hand, the many frameworks and schemes proposed in the literature for theory update and revision are plagued by serious complexity-theoretic impediments, even in the Horn case, as was pointed out in [6], and is further demonstrated in the present paper. More fundamentally, these schemes are not inductive, in that they may lose in a single update any positive properties of the represented sets of formulas (small size, Horn structure, etc.). In this paper 1 we propose a new scheme, incremental recompilation, which combines Horn approximation and model-based updates; this scheme is inductive and very efficient, free of...