Reasoning about Explanations for Negative Query Answers in DL-Lite

In order to meet usability requirements, most logic-based applications provide explanation facilities for reasoning services. This holds also for Description Logics, where research has focused on the explanation of both TBox reasoning and, more recently, query answering. Besides explaining the presence of a tuple in a query answer, it is important to explain also why a given tuple is missing. We address the latter problem for instance and conjunctive query answering over DL-Lite ontologies by adopting abductive reasoning; that is, we look for additions to the ABox that force a given tuple to be in the result. As reasoning tasks we consider existence and recognition of an explanation, and relevance and necessity of a given assertion for an explanation. We characterize the computational complexity of these problems for arbitrary, subset minimal, and cardinality minimal explanations

Description Logic for Scene Understanding at the Example of Urban Road Intersections

Understanding a natural scene on the basis of external sensors is a task yet to be solved by computer algorithms. The present thesis investigates the suitability of a particular family of explicit, formal representation and reasoning formalisms for this task, which are subsumed under the term Description Logic

An evaluation methodology and framework for semantic web services technology

Software engineering has been driven over decades by the trend towards component based development and loose coupling. Service oriented architectures and Web Services in particular are the latest product of this long-reaching development. Semantic Web Services (SWS) apply the paradigms of the Semantic Web to Web Services to allow more flexible and dynamic service usages. Numerous frameworks to realize SWS have been put forward in recent years but their relative advantages and general maturity are not easy to assess. This dissertation presents a solution to this issue. It defines a general methodology and framework for SWS technology evaluation as well as concrete benchmarks to assess the functional scope and performance of various approaches. The presented benchmarks have been executed within international evaluation campaign. The thesis thus comprehensively covers theoretical, methodological as well as practical results regarding the evaluation and assessment of SWS technologies

Proceedings of the 11th Workshop on Nonmonotonic Reasoning

These are the proceedings of the 11th Nonmonotonic Reasoning Workshop. The aim of this series is to bring together active researchers in the broad area of nonmonotonic reasoning, including belief revision, reasoning about actions, planning, logic programming, argumentation, causality, probabilistic and possibilistic approaches to KR, and other related topics. As part of the program of the 11th workshop, we have assessed the status of the field and discussed issues such as: Significant recent achievements in the theory and automation of NMR; Critical short and long term goals for NMR; Emerging new research directions in NMR; Practical applications of NMR; Significance of NMR to knowledge representation and AI in general

a new matchmaking approach based on abductive conjunctive query answering

To perform matchmaking in Web-based scenarios where data are often incomplete, we propose an extended conjunctive query answering (CQA) problem, called abductive CQA problem, in Description Logic ontologies. Given a consistent ontology and a conjunctive query, the abductive CQA problem computes all abductive answers to the query in the ontology. An abductive answer is an answer to the query in some consistent ontology enlarged from the given one by adding a bounded number of individual assertions, where the individual assertions that can be added are confined by user-specified concept or role names. We also propose a new approach to matchmaking based on the abductive CQA semantics, in which offer information is expressed as individual assertions, request information is expressed as conjunctive queries, and matches for a request are defined as abductive answers to a conjunctive query that expresses the request. We propose a sound and complete method for computing all abductive answers to a conjunctive query in an ontology expressed in the Description Logic Program fragment of OWL 2 DL with the Unique Name Assumption. The feasibility of this method is demonstrated by a real-life application, rental matchmaking, which handles requests for renting houses. © 2012 Springer-Verlag.To perform matchmaking in Web-based scenarios where data are often incomplete, we propose an extended conjunctive query answering (CQA) problem, called abductive CQA problem, in Description Logic ontologies. Given a consistent ontology and a conjunctive query, the abductive CQA problem computes all abductive answers to the query in the ontology. An abductive answer is an answer to the query in some consistent ontology enlarged from the given one by adding a bounded number of individual assertions, where the individual assertions that can be added are confined by user-specified concept or role names. We also propose a new approach to matchmaking based on the abductive CQA semantics, in which offer information is expressed as individual assertions, request information is expressed as conjunctive queries, and matches for a request are defined as abductive answers to a conjunctive query that expresses the request. We propose a sound and complete method for computing all abductive answers to a conjunctive query in an ontology expressed in the Description Logic Program fragment of OWL 2 DL with the Unique Name Assumption. The feasibility of this method is demonstrated by a real-life application, rental matchmaking, which handles requests for renting houses. © 2012 Springer-Verlag

On the role of Computational Logic in Data Science: representing, learning, reasoning, and explaining knowledge

In this thesis we discuss in what ways computational logic (CL) and data science (DS) can jointly contribute to the management of knowledge within the scope of modern and future artificial intelligence (AI), and how technically-sound software technologies can be realised along the path. An agent-oriented mindset permeates the whole discussion, by stressing pivotal role of autonomous agents in exploiting both means to reach higher degrees of intelligence. Accordingly, the goals of this thesis are manifold. First, we elicit the analogies and differences among CL and DS, hence looking for possible synergies and complementarities along 4 major knowledge-related dimensions, namely representation, acquisition (a.k.a. learning), inference (a.k.a. reasoning), and explanation. In this regard, we propose a conceptual framework through which bridges these disciplines can be described and designed. We then survey the current state of the art of AI technologies, w.r.t. their capability to support bridging CL and DS in practice. After detecting lacks and opportunities, we propose the notion of logic ecosystem as the new conceptual, architectural, and technological solution supporting the incremental integration of symbolic and sub-symbolic AI. Finally, we discuss how our notion of logic ecosys- tem can be reified into actual software technology and extended towards many DS-related directions

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation