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When owl:sameas isn’t the same: An analysis of identity links on the semantic web
 In Linked Data on the Web (LDOW2010
, 2010
"... In Linked Data, the use of owl:sameAs is ubiquitous in ‘interlinking ’ datasets. However, there is a lurking suspicion within the Linked Data community that this use of owl:sameAs may be somehow incorrect, in particular with regards to its interactions with inference. In fact, owl:sameAs can be co ..."
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Cited by 53 (1 self)
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In Linked Data, the use of owl:sameAs is ubiquitous in ‘interlinking ’ datasets. However, there is a lurking suspicion within the Linked Data community that this use of owl:sameAs may be somehow incorrect, in particular with regards to its interactions with inference. In fact, owl:sameAs can be considered just one type of ‘identity link, ’ a link that declares two items to be identical in some fashion. After reviewing the definitions and history of the problem of identity in philosophy and knowledge representation, we outline four alternative readings of owl:sameAs, showing with examples how it is being (ab)used on the Web of data. Then we present possible solutions to this problem by introducing alternative identity links that rely on named graphs.
What is an Inference Rule?
 Journal of Symbolic Logic
, 1992
"... What is an inference rule? This question does not have a unique answer. One usually nds two distinct standard answers in the literature: validity inference ( ` v ' if for every substitution , the validity of [] entails the validity of [']), and truth inference ( ` t ' if for every substitution , ..."
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Cited by 19 (2 self)
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What is an inference rule? This question does not have a unique answer. One usually nds two distinct standard answers in the literature: validity inference ( ` v ' if for every substitution , the validity of [] entails the validity of [']), and truth inference ( ` t ' if for every substitution , the truth of [] entails the truth of [']). In this paper we introduce a general semantic framework that allows us to investigate the notion of inference more carefully. Validity inference and truth inference are in some sense the extremal points in our framework. We investigate the relationship between various types of inference in our general framework, and consider the complexity of deciding if an inference rule is sound, in the context of a number of logics of interest: classical propositional logic, a nonstandard propositional logic, various propositional modal logics, and rstorder logic.
Knowledge Representation and Classical Logic
"... Mathematical logicians had developed the art of formalizing declarative knowledge long before the advent of the computer age. But they were interested primarily in formalizing mathematics. Because of the important role of nonmathematical knowledge in AI, their emphasis was too narrow from the perspe ..."
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Cited by 10 (4 self)
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Mathematical logicians had developed the art of formalizing declarative knowledge long before the advent of the computer age. But they were interested primarily in formalizing mathematics. Because of the important role of nonmathematical knowledge in AI, their emphasis was too narrow from the perspective of knowledge representation, their formal languages were not sufficiently expressive. On the other hand, most logicians were not concerned about the possibility of automated reasoning; from the perspective of knowledge representation, they were often too generous in the choice of syntactic constructs. In spite of these differences, classical mathematical logic has exerted significant influence on knowledge representation research, and it is appropriate to begin this handbook with a discussion of the relationship between these fields. The language of classical logic that is most widely used in the theory of knowledge representation is the language of firstorder (predicate) formulas. These are the formulas that John McCarthy proposed to use for representing declarative knowledge in his advice taker paper [176], and Alan Robinson proposed to prove automatically using resolution [236]. Propositional logic is, of course, the most important subset of firstorder logic; recent
Modelling Social Interaction Attitudes in MultiAgent Systems
, 2001
"... Abstract 2 Most autonomous agents are situated in a social context and need to interact with other agents (both human and artificial) to complete their problem solving objectives. Such agents are usually capable of performing a wide range of actions and engaging in a variety of social interactions. ..."
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Cited by 5 (2 self)
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Abstract 2 Most autonomous agents are situated in a social context and need to interact with other agents (both human and artificial) to complete their problem solving objectives. Such agents are usually capable of performing a wide range of actions and engaging in a variety of social interactions. Faced with this variety of options, an agent must decide what to do. There are many potential decision making functions that could be employed to make the choice. Each such function will have a different effect on the success of the individual agent and of the overall system in which it is situated. To this end, this thesis examines agents ’ decision making functions to ascertain their likely properties and attributes. A novel framework for characterising social decision making is presented which provides explicit reasoning about the potential benefits of the individual agent, particular subgroups of agents or the overall system. This framework enables multifarious social interaction attitudes to be identified and defined; ranging from the purely selfinterested to the purely altruistic. In particular, however, the focus is on the spectrum of socially responsible agent behaviours in which agents attempt to balance their own needs with those of the overall system. Such behaviour aims to ensure that both the agent and the overall system perform well.
Motivations for MathLang
, 2005
"... FOMCAF13 What do we want? Open borders for productive collaboration or that we each stick to our borders without including and benefiting from other input? Do we want war+destruction or solid foundations for wisdom and prosperity? • Do we believe in the chosen framework? Should all the world believe ..."
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Cited by 3 (0 self)
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FOMCAF13 What do we want? Open borders for productive collaboration or that we each stick to our borders without including and benefiting from other input? Do we want war+destruction or solid foundations for wisdom and prosperity? • Do we believe in the chosen framework? Should all the world believe in the same framework? Does one framework fit all? Can such a framework exist? • Think of Capitalism, Communism, dictatorship, nationalism, etc... Which one worked in history? • But then, if we are committed to pluralism, are we in danger of being wiped out because being inclusive may well lead to contradictions? • Oscar Wilde: I used to think I was indecisive, but now I’m not sure anymore. FOMCAF13 1Things are not as somber: There is no perfect framework, but some can be invaluable • De Bruijn used to proudly announce: I did it my way. • I quote Dirk van Dalen: The Germans have their 3 B’s, but we Dutch too have our 3 B’s: Beth, Brouwer and de Bruijn. FOMCAF13 2There is a fourth B:
Resolution Proofs and DLL Algorithms with Clause Learning
, 2007
"... This thesis analyzes the connections between resolution proofs and satisfiability search procedures. It is well known that DLL search algorithms that do not use learning are equivalent to treelike resolution in terms of proof complexity. To generalize this result to DLL algorithms that use learning ..."
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Cited by 2 (1 self)
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This thesis analyzes the connections between resolution proofs and satisfiability search procedures. It is well known that DLL search algorithms that do not use learning are equivalent to treelike resolution in terms of proof complexity. To generalize this result to DLL algorithms that use learning, two natural generalizations of regular resolution that are based on resolution trees with lemmas (RTL) are introduced. It is shown that daglike resolution is equivalent to these resolution refinements when there is no regularity condition. On the other hand an exponential separation between the regular versions (regular weak resolution trees with input lemmas and regular weak resolution trees with lemmas) and regular daglike resolution is given. It is proved that executions of DLL algorithms that use learning based on the conflict graph and unit propagation, like most of the current state of the art SATsolvers, can be simulated by regular WRTL. Inspired by this simulation, a new generalization of learning in DLL algorithms, which is polynomially equivalent to regular WRTL, is presented. This algorithm can simulate general