Traditional object-oriented programming languages can be difficult to use when working with ontologies, leading to the creation of domain-specific languages designed specifically for ontology processing. Prolog, with ...
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Traditional object-oriented programming languages can be difficult to use when working with ontologies, leading to the creation of domain-specific languages designed specifically for ontology processing. Prolog, with its logic-based, declarative semantics offers many advantages as a host programming language for querying and processing OWL2 ontologies. The SWI-Prolog semweb library provides some support for OWL but until now there has been a lack of any library providing direct and comprehensive support for OWL2. We have developed Thea, a library based directly on the OWL2 functionalstyle syntax, allowing storage and manipulation of axioms as a Prolog database. Thea can translate ontologies to Description logic programs but the emphasis is on using Prolog as an application programming and processing language rather than a reasoning engine. Thea offers the ability to seamless connect to the java OWL API and OWLLink servers. Thea also includes support for SWRL. In this paper we provide examples of using Thea for processing ontologies, and compare the results to alternative methods. Thea is available from GitHub: http://***/vangelisv/ thea.
This paper presents an abstract treatment of the foundations of rewriting logic, generalising in three ways: an arbitrary 2-category plays the role of the specific 2-category Cat;the foundations are rendered fully ind...
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Hypermedia technology has aroused considerable interest in didactic environments, owing to its versatility in realizing didactic software where the attention is shifted away from the teaching towards the learning proc...
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Existing cognitive agent programming languages that are based on the BDI model employ logical representation and reasoning for implementing the beliefs of agents. In these programming languages, the beliefs are assume...
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ISBN:
(纸本)3540331069
Existing cognitive agent programming languages that are based on the BDI model employ logical representation and reasoning for implementing the beliefs of agents. In these programming languages, the beliefs are assumed to be certain, i.e. an implemented agent can believe a proposition or not. These programming languages fail to capture the underlying uncertainty of the agent's beliefs which is essential for many real world agent applications. We introduce Dempster-Shafer theory as a convenient method to model uncertainty in agent's beliefs. We show that the computational complexity of Dempster's Rule of Combination can be controlled. In particular, the certainty value of a proposition can be deduced in linear time from the beliefs of agents, without having to calculate the combination of Dempster-Shafer mass functions.
PIE is a Prolog-embedded environment for automated reasoning on the basis of first-order logic. Its main focus is on formulas, as constituents of complex formalizations that are structured through formula macros, and ...
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This paper extends a programming language for implementing cognitive agents with the capability to explicitly represent beliefs and reason about them. In this programming language, the beliefs of agents are implemente...
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ISBN:
(纸本)3540331069
This paper extends a programming language for implementing cognitive agents with the capability to explicitly represent beliefs and reason about them. In this programming language, the beliefs of agents are implemented by modal logic programs, where beliefs are represented by explicit modal operators. A distinction is made between a belief base language that can be used to represent an agent's beliefs, and a belief query language that can be used to express queries to the agent's belief base. We adopt and modify a proof procedure that decides if a belief query formula is derivable from the belief base of an agent. We show that the presented proof procedure is sound.
We present a novel approach to debugging expressively rich knowledgerepresentation and reasoning (KRR) logic Rulelog. Rulelog is an extended form of declarative logic programs (LP) under the wellfounded semantics, wh...
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We present a novel approach to debugging expressively rich knowledgerepresentation and reasoning (KRR) logic Rulelog. Rulelog is an extended form of declarative logic programs (LP) under the wellfounded semantics, which allows higher-order logic formulas as axioms in combination with defeasibility mechanisms that include rule cancellation and priorities, along with default and explicit negation. Rulelog also supports strong knowledge interchange with all current major semantic web standards for logical KRR. Rulelog has been implemented in Flora-2 and Silk, both on top of XSB;and (less completely) in Cyc. The debugging approach described here is part of an integrated development environment, most fully implemented in Silk. The approach includes: reasoning trace analysis, based on tabled LP inferencing tables and forestlog;and justification graphs, which treat why-not and defeasibility as well as provenance. The reasoning trace analysis treats performance and runaway computations, including non-termination as well as classic subgoal-ordering issues that arise in database query optimization. Non-termination can be prevented entirely by leveraging the restraint (bounded rationality) feature of Rulelog. Revision/authoring of knowledge is interactive, based on a rapid edit-test-inspect loop and incremental truth maintenance.
LIFE is an experimental programming language proposing to integrate logicprogramming, functional programming, and object-oriented programming. It replaces first-order terms with ψ-terms, data structures which allow ...
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In this article, we define a new variant of Cai-Furer-Immerman construction. With this construction and some conditions of Dawar and Richerby, we are able to show that inflationary fixed point logic with counting (IFP...
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ISBN:
(纸本)9783642022692
In this article, we define a new variant of Cai-Furer-Immerman construction. With this construction and some conditions of Dawar and Richerby, we are able to show that inflationary fixed point logic with counting (IFP+C) does not capture PTIME on the class of balanced graphs.
This paper proposes a simple high-level programming language, endowed with resources that help encoding self-modifying programs. With this purpose, a conventional imperative language syntax (not explicitly stated in t...
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This paper proposes a simple high-level programming language, endowed with resources that help encoding self-modifying programs. With this purpose, a conventional imperative language syntax (not explicitly stated in this paper) is incremented with special commands and statements forming an adaptive layer specially designed with focus on the dynamical changes to be applied to the code at run-time. The resulting language allows programmers to easily specify dynamic changes to their own program's code. Such a language succeeds to allow programmers to effortless describe the dynamic logic of their adaptive applications. In this paper, we describe the most important aspects of the design and implementation of such a language. A small example is finally presented for illustration purposes.
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