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35
Explanation and Prediction: An Architecture for Default and Abductive Reasoning
 Computational Intelligence
, 1993
"... Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of ..."
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Cited by 139 (16 self)
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Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given. Key words: defaults, conjectures, explanation, prediction, abduction, dialectics, logic, nonmonotonicity, theory formation Explanation and Prediction 2 1 Introduction One way to do research i...
Perception as Abduction: Turning Sensor Data into Meaningful Representation
 Cognitive Science
, 2005
"... This article presents a formal theory of robot perception as a form of abduction. The theory pins down the process whereby lowlevel sensor data is transformed into a symbolic representation of the external world, drawing together aspects such as incompleteness, topdown information flow, active per ..."
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Cited by 45 (2 self)
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This article presents a formal theory of robot perception as a form of abduction. The theory pins down the process whereby lowlevel sensor data is transformed into a symbolic representation of the external world, drawing together aspects such as incompleteness, topdown information flow, active perception, attention, and sensor fusion in a unifying framework. In addition, a number of themes are identified that are common to both the engineer concerned with developing a rigorous theory of perception, such as the one on offer here, and the philosopher of mind who is exercised by questions relating to mental representation and intentionality.
(ML)²: A formal language for KADS models of expertise
, 1993
"... This paper reports on an investigation into a formal language for specifying kads models of expertise. After arguing the need for and the use of such formal representations, we discuss each of the layers of a kads model of expertise in the subsequent sections, and define the formal constructions tha ..."
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Cited by 35 (9 self)
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This paper reports on an investigation into a formal language for specifying kads models of expertise. After arguing the need for and the use of such formal representations, we discuss each of the layers of a kads model of expertise in the subsequent sections, and define the formal constructions that we use to represent the kads entities at every layer: ordersorted logic at the domain layer, metalogic at the inference layer, and dynamiclogic at the task layer. All these constructions together make up (ml) 2 , the language that we use to represent models of expertise. We illustrate the use of (ml) 2 in a small example model. We conclude by describing our experience to date with constructing such formal models in (ml) 2 , and by discussing some open problems that remain for future work. 1 Introduction One of the central concerns of "knowledge engineering" is the construction of a model of some problem solving behaviour. This model should eventually lead to the construction of a...
KnowledgeBased Disambiguation for Machine Translation
 MINDS AND MACHINES
, 1994
"... The resolution of ambiguities is one of the central problems for Machine Translation. In this paper we propose a knowledgebased approach to disambiguation which uses Description Logics (DL) as representation formalism. We present the process of anaphora resolution implemented in the Machine Transla ..."
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Cited by 17 (5 self)
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The resolution of ambiguities is one of the central problems for Machine Translation. In this paper we propose a knowledgebased approach to disambiguation which uses Description Logics (DL) as representation formalism. We present the process of anaphora resolution implemented in the Machine Translation system FAST and show how the DL system BACK is used to support disambiguation. The disambiguation strategy uses factors representing syntactic, semantic, and conceptual constraints with different weights to choose the most adequate antecedent candidate. We show how these factors can be declaratively represented as defaults in BACK. Disambiguation is then achieved by determining the interpretation that yields a qualitatively minimal number of exceptions to the defaults, and can thus be formalized as exception minimization.
MetaLevel Inference Systems
, 1991
"... 1.1 Goals of this book................................ 13 ..."
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Cited by 16 (4 self)
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1.1 Goals of this book................................ 13
The Bayesian basis of common sense medical diagnosis
 In Proceedings of the AAAI83
, 1983
"... While the mathematics of conditional probabilities in general, and Bayesian statistics in particular, would seem to offer a foundation for medical diagnosis (and other cases of decision making under uncertainty), such ..."
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Cited by 9 (0 self)
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While the mathematics of conditional probabilities in general, and Bayesian statistics in particular, would seem to offer a foundation for medical diagnosis (and other cases of decision making under uncertainty), such
Belief rulebase inference methodology using the evidential reasoning approach  RIMER
 IEEE TRANS. ON SYS
, 2006
"... In this paper, a generic rulebase inference methodology using the evidential reasoning (RIMER) approach is proposed. Existing knowledgebase structures are first examined, and knowledge representation schemes under uncertainty are then briefly analyzed. Based on this analysis, a new knowledge repr ..."
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Cited by 9 (4 self)
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In this paper, a generic rulebase inference methodology using the evidential reasoning (RIMER) approach is proposed. Existing knowledgebase structures are first examined, and knowledge representation schemes under uncertainty are then briefly analyzed. Based on this analysis, a new knowledge representation scheme in a rule base is proposed using a belief structure. In this scheme, a rule base is designed with belief degrees embedded in all possible consequents of a rule. Such a rule base is capable of capturing vagueness, incompleteness, and nonlinear causal relationships, while traditional if–then rules can be represented as a special case. Other knowledge representation parameters such as the weights of both attributes and rules are also investigated in the scheme. In an established rule base, an input to an antecedent attribute is transformed into a belief distribution. Subsequently, inference in such a rule base is implemented using the evidential reasoning (ER) approach. The scheme is further extended to inference in hierarchical rule bases. A numerical study is provided to illustrate the potential applications of the proposed methodology.
Designing visual languages for description logics
 Journal of Logic, Language and Information
"... Semantic networks were developed in cognitive science and artificial intelligence studies as graphical knowledge representation and inference tools emulating human thought processes. Formal analysis of the representation and inference capabilities of the networks modeled them as subsets of standard ..."
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Cited by 8 (6 self)
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Semantic networks were developed in cognitive science and artificial intelligence studies as graphical knowledge representation and inference tools emulating human thought processes. Formal analysis of the representation and inference capabilities of the networks modeled them as subsets of standard firstorder logic (FOL), restricted in the operations allowed in order to ensure the tractability that seemed to characterize human reasoning capabilities. The graphical network representations were modeled as providing a visual language for the logic. Subsets of FOL targeted on knowledge representation came to be called description logics, and research on these logics has focused on issues of tractability of subsets with differing representation capabilities, and on the implementation of practical inference systems achieving the best possible performance. Semantic network research has kept pace with these developments, providing visual languages for knowledge entry, editing, and presenting the results of inference, that translate unambiguously to the underlying description logics. This paper discusses the design issues for such semantic network formalisms, and illustrates them through detailed examples of significant generic knowledge structures analyzed in the literature, including determinables, contrast sets, genus/differentiae, taxonomies, faceted taxonomies, cluster concepts, family resemblances, graded concepts, frames, definitions, rules, rules with exceptions, essence and state assertions, opposites and contraries, relevance, and so on. Such examples provide important test material for any visual language formalism for logic.
What’s in a model? Epistemological analysis of logic programming
 Proceedings of the 9th International Conference on PrinICLP 2012 A Tarskian Informal Semantics for ASP ciples of Knowledge Representation and Reasoning
, 2004
"... It is commonly believed that the meaning of a formal declarative knowledge representation language is determined by its formal semantics. This is not quite so. This paper shows an epistemological ambiguity that arises in the context of logic programming. Several different logic programming formali ..."
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Cited by 8 (3 self)
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It is commonly believed that the meaning of a formal declarative knowledge representation language is determined by its formal semantics. This is not quite so. This paper shows an epistemological ambiguity that arises in the context of logic programming. Several different logic programming formalisms and semantics have been proposed. Hence, logic programming can be seen as an overlapping family of formal logics, each induced by a pair of a formal syntax and a formal semantics. We would expect that (a) each such pair has a unique declarative reading and (b) for a program in the intersection of several formal LP logics with the same formal semantics in each of them, its declarative reading is the same in each of them. I show in this paper that neither (a) nor (b) holds. The paper investigates the causes and the consequences of this phenomenon and points out some directions to overcome the ambiguity.