312 research outputs found
Deploying ontologies in software design
In this thesis we will be concerned with the relation between ontologies and software
design. Ontologies are studied in the artificial intelligence community as a means to
explicitly represent standardised domain knowledge in order to enable knowledge shar¬
ing and reuse. We deploy ontologies in software design with emphasis on a traditional
software engineering theme: error detection. In particular, we identify a type of error
that is often difficult to detect: conceptual errors. These are related to the description
of the domain whom which the system will operate. They require subjective knowledge
about correct forms of domain description to detect them. Ontologies provide these
forms of domain description and we are interested in applying them and verify their
correctness(chapter 1). After presenting an in depth analysis of the field of ontologies
and software testing as conceived and implemented by the software engineering and
artificial intelligence communities(chapter 2), we discuss an approach which enabled
us to deploy ontologies in the early phases of software development (i.e., specifications)
in order to detect conceptual errors (chapter 3). This is based on the provision of ontological axioms which are used to verify conformance of specification constructs to
the underpinning ontology. To facilitate the integration of ontology with applications
that adopt it we developed an architecture and built tools to implement this form of
conceptual error check(chapter 4). We apply and evaluate the architecture in a variety
of contexts to identify potential uses (chapter 5). An implication of this method for de¬
ploying ontologies to reason about the correctness of applications is to raise our trust
in the given ontologies. However, when the ontologies themselves are erroneous we
might fail to reveal pernicious discrepancies. To cope with this problem we extended
the architecture to a multi-layer form(chapter 4) which gives us the ability to check the
ontologies themselves for correctness. We apply this multi-layer architecture to cap¬
ture errors found in a complex ontologies lattice(chapter 6). We further elaborate on
the weaknesses in ontology evaluation methods and employ a technique stemming from
software engineering, that of experience management, to facilitate ontology testing and
deployment(chapter 7). The work presented in this thesis aims to improve practice in
ontology use and identify areas to which ontologies could be of benefits other than the
advocated ones of knowledge sharing and reuse(chapter 8)
Logic-Based Specification Languages for Intelligent Software Agents
The research field of Agent-Oriented Software Engineering (AOSE) aims to find
abstractions, languages, methodologies and toolkits for modeling, verifying,
validating and prototyping complex applications conceptualized as Multiagent
Systems (MASs). A very lively research sub-field studies how formal methods can
be used for AOSE. This paper presents a detailed survey of six logic-based
executable agent specification languages that have been chosen for their
potential to be integrated in our ARPEGGIO project, an open framework for
specifying and prototyping a MAS. The six languages are ConGoLog, Agent-0, the
IMPACT agent programming language, DyLog, Concurrent METATEM and Ehhf. For each
executable language, the logic foundations are described and an example of use
is shown. A comparison of the six languages and a survey of similar approaches
complete the paper, together with considerations of the advantages of using
logic-based languages in MAS modeling and prototyping.Comment: 67 pages, 1 table, 1 figure. Accepted for publication by the Journal
"Theory and Practice of Logic Programming", volume 4, Maurice Bruynooghe
Editor-in-Chie
Recommended from our members
Multiple Viewpoints for Tutoring Systems.
This thesis investigates the issue of how a tutoring system, intelligent or otherwise, may be designed to utilise multiple viewpoints on the domain being tutored, and what benefits may accrue from this. The issue was relevant to earlier systems, such as WHY (Stevens et al. 1979) and STEAMER (Hollan et al. 1984).
The relevant literature is reviewed, and criteria which must be met by our implementation of viewpoints are established. Viewpoints are conceptualised as pre-defined structures which can be represented in a tutoring system with the potential to increase its effectiveness and adaptability. A formalism is proposed where inferences are drawn from a model by a range of operators. The application of this combination to problems and goals is to be described heuristically. This formulation is then related to the educational philosophy of Cognitive Apprenticeship. The formalism is tested and refined in a protocol analysis study which leads to the definition of three classes of operators.
The viewpoint structure is used to produce a detailed formulation of the domain of Prolog debugging for novices, with the goal that students should learn how different bugs may be localised using different viewpoints. Three models of execution are defined, based on those described by Bundy et al. (1985). These are mapped onto a restricted catalogue of bugs by specifying a number of conventions which produce a simplified and consistent domain suited to the needs of novices.
VIPER, a tutoring system which can itself accomplish and explain the relevant domain tasks, is described. VIPER is based on a meta-interpreter which produces detailed execution histories which are then analysed. An evaluation of VIPER is reported, with generally favourable results.
VIPER is discussed in relation to the research goals, the usefulness of Cognitive Apprenticeship in supporting such a design, and possible future work. This discussion exemplifies the use of established student modeling techniques, the implementation of other viewpoints on Prolog, and the application of the design strategy to other domains. Claims are made in relation to the formulation of viewpoints, the architecture of VIPER, and the relevance of Cognitive Apprenticeship to the use of multiple viewpoints
The development of an expert system shell with a mixed knowledge representation, explicit control of reasoning and a truth maintenance system
Bibliography: pages 227-236.This thesis concentrates on several important issues in expert system research, namely - representation of knowledge - control of reasoning - implementation of non-monotonic logics via truth maintenance systems. There are three parts to this thesis. PART1 covers the background research in the above mentioned topics. PART2 discusses the WISE system and the way in which research from PART1 was applied to the development of the WISE shell. PART3 considers the features of other expert system shells
Kiel Declarative Programming Days 2013
This report contains the papers presented at the Kiel Declarative Programming Days 2013, held in Kiel (Germany) during September 11-13, 2013. The Kiel Declarative Programming Days 2013 unified the following events: * 20th International Conference on Applications of Declarative Programming and Knowledge Management (INAP 2013) * 22nd International Workshop on Functional and (Constraint) Logic Programming (WFLP 2013) * 27th Workshop on Logic Programming (WLP 2013) All these events are centered around declarative programming, an advanced paradigm for the modeling and solving of complex problems. These specification and implementation methods attracted increasing attention over the last decades, e.g., in the domains of databases and natural language processing, for modeling and processing combinatorial problems, and for high-level programming of complex, in particular, knowledge-based systems
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
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