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21
A Cognitive Theory of Graphical and Linguistic Reasoning: Logic and Implementation
, 1995
"... We discuss external and internal graphical and linguistic representational systems. We argue that a cognitive theory of peoples' reasoning performance must account for (a) the logical equivalence of inferences expressed in graphical and linguistic form; and (b) the implementational differences th ..."
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Cited by 106 (11 self)
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We discuss external and internal graphical and linguistic representational systems. We argue that a cognitive theory of peoples' reasoning performance must account for (a) the logical equivalence of inferences expressed in graphical and linguistic form; and (b) the implementational differences that affect facility of inference. Our theory proposes that graphical representations limit abstraction and thereby aid processibility. We discuss the ideas of specificity and abstraction, and their cognitive relevance. Empirical support comes from tasks involving (i) the manipulation of external graphics; and (ii) no external graphics. For (i), we take Euler's Circles, provide a novel computational reconstruction, show how it captures abstractions, and contrast it with earlier construals, and with Mental Models' representations. We demonstrate equivalence of the graphical Euler system, and the nongraphical Mental Models system. For (ii), we discuss text comprehension, and the mental ...
Representing Incomplete Knowledge in Abductive Logic Programming
 In Proc. of the International Symposium on Logic Programming
, 1993
"... Recently, Gelfond and Lifschitz presented a formal language for representing incomplete knowledge on actions and states, and a sound translation from this language to extended logic programming. We present an alternative translation to abductive logic programming with integrity constraints and prove ..."
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Cited by 58 (10 self)
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Recently, Gelfond and Lifschitz presented a formal language for representing incomplete knowledge on actions and states, and a sound translation from this language to extended logic programming. We present an alternative translation to abductive logic programming with integrity constraints and prove the soundness and completeness. In addition, we show how an abductive procedure can be used, not only for explanation, but also for deduction and proving satisfiability under uncertainty. From a more general perspective, this work can be viewed as asuccessfulexperiment in the declarative representation of and automated reasoning on incomplete knowledge using abductive logic programming. 1
SLDNFA: an abductive procedure for abductive logic programs
, 1997
"... We present SLDNFA, an extension of SLDNFresolution for abductive reasoning on abductive logic programs. SLDNFA solves the floundering abduction problem: nonground abductive atoms can be selected. SLDNFA provides also a partial solution for the floundering negation problem. Different abductive a ..."
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Cited by 55 (13 self)
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We present SLDNFA, an extension of SLDNFresolution for abductive reasoning on abductive logic programs. SLDNFA solves the floundering abduction problem: nonground abductive atoms can be selected. SLDNFA provides also a partial solution for the floundering negation problem. Different abductive answers can be derived from an SLDNFArefutation; these answers provide different compromises between generality and comprehensibility. Two extensions of SLDNFA are proposed which satisfy stronger completeness results. The soundness of SLDNFA and its extensions is proven. Their completeness for minimal solutions with respect to implication, cardinality and set inclusion is investigated. The formalisation of SLDNFA presented here is an update of an older version presented in [13] and does not rely on skolemisation of abductive atoms. 1
Multiagent Reasoning with Belief Contexts II: Elaboration Tolerance
 Intelligent Agents: Proceedings of 1994 Workshop on Agent Theories, Architectures, and Languages, number 890 in Lecture Notes in Computer Science
, 1994
"... As discussed in previous papers, belief contexts are a powerful and appropriate formalism for the representation and implementation of propositional attitudes in a multiagent environment. In this paper we show that a formalization using belief contexts is also elaboration tolerant. That is, it is a ..."
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Cited by 51 (6 self)
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As discussed in previous papers, belief contexts are a powerful and appropriate formalism for the representation and implementation of propositional attitudes in a multiagent environment. In this paper we show that a formalization using belief contexts is also elaboration tolerant. That is, it is able to cope with minor changes to input problems without major revisions. Elaboration tolerance is a vital property for building situated agents: it allows for adapting and reusing a previous problem representation in different (but related) situations, rather than building a new representation from scratch. We substantiate our claims by discussing a number of variations to a paradigmatic case study, the Three Wise Men problem. Introduction Belief contexts (Giunchiglia 1993; Giunchiglia & Serafini 1994; Giunchiglia et al. 1993) are a formalism for the representation of propositional attitudes. Their basic feature is modularity: knowledge can be distributed into different and separated mod...
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 38 (1 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...
The naive physics perplex
 AI Magazine
, 1998
"... The \Naive Physics Manifesto " of Pat Hayes (1978) proposes a largescale project of developing a formal theory encompassing the entire knowledge of physics of naive reasoners, expressed in a declarative symbolic form. The theory is organized in clusters of closely interconnected concepts and a ..."
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Cited by 25 (6 self)
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The \Naive Physics Manifesto " of Pat Hayes (1978) proposes a largescale project of developing a formal theory encompassing the entire knowledge of physics of naive reasoners, expressed in a declarative symbolic form. The theory is organized in clusters of closely interconnected concepts and axioms. More recent work in the representation of commonsense physical knowledge has followed a somewhat di erent methodology. The goal has been to develop a competence theory powerful enough to justify commonsense physical inferences, and the research is organized in microworlds, each microworld covering a small range of physical phenomena. In this paper we compare the advantages and disadvantages of the two approaches. Three Scenarios Consider the following scenario: Common sense is a wild thing, savage, and beyond rules.
Limited Reasoning in FirstOrder Knowledge Bases
 Artificial Intelligence
, 1994
"... In traditional formal approaches to knowledge representation, agents are assumed to believe all the logical consequences of their knowledge bases. As a result, reasoning in the firstorder case becomes undecidable. Since real agents are constrained by resource limitations, it seems appropriate to lo ..."
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Cited by 21 (2 self)
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In traditional formal approaches to knowledge representation, agents are assumed to believe all the logical consequences of their knowledge bases. As a result, reasoning in the firstorder case becomes undecidable. Since real agents are constrained by resource limitations, it seems appropriate to look for weaker forms of reasoning with better computational properties. One way to approach the problem is by modeling belief. Reasoning can then be understood as the question whether a belief follows from believing the sentences in the knowledge base. This paper proposes...
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