Josephson, J.R., Josephson, S.J. Abductive Inference: Computation, Philosophy, Technology. New York, Cambridge University Press, (1994).  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... Senegal beats France in the 2002 World Cup ) To fully exploit the variety of descriptions in the MPEG 7 representation what is required is a system that can utilise and reason about the different levels of description. Our proposed methodology is based on the notion of abductive explanation [4]. Given a small subset of data that the user has identified as being of interest, this form of knowledge manipulation generates explanations of why the data may be relevant to a searcher. An explanation is a description of the data containing elements from any of the MPEG 7 description layers ....

....from each level. What we propose in this research is an integrated approach to the retrieval and presentation of search results; an approach that reduces the cognitive effort a user must expend in describing what information they require. We base this approach on the notion of abductive inference [4]. A number of these are surveyed in [3] 3 Abductive inference Abductive inference is specifically designed to provide explanations of complex data. In our framework the data to be explained are the relevant video segments selected by the user. From this set of video segments an abductive ....

J.R. Josephson and S.G. Josephson (ed). Abductive Inference: Computation, Philosophy, Technology. Cambridge University Press. 1994.

....The term abduction was introduced by the logician and philosopher C.S. Pierce (1839 1914) who defined it as the inference process of forming a hypothesis that explains given observed phenomena [77] Often abduction has been defined broadly as any form of inference to the best explanation [47] where best refers to the fact that the generated hypothesis is subjected to some optimality criterion. This very broad definition covers a wide range of di#erent phenomena involving some form of hypothetical reasoning. Studies of abduction range from philosophical treatments of human scientific ....

....the predicates that may appear in it) This view defines an abductive explanation of an observation as a formula which logically entails the observation. However, some have argued, sometimes with good reasons, that it is more natural to view an explanation as a cause for the observation [47]. A well known example is as follows [92] the disease paresis is caused by a latent untreated form of syphilis. The probability that latent untreated syphilis leads to paresis is only 25 . Note that in this context, the direction of entailment and causality are opposite: syphilis is the cause of ....

J.R. Josephson and S.G. Josephson, editors. Abductive Inference: Computation, Philosophy, Technology. New York: Cambridge University Press, 1994.

....quality conditions such as (a form of) minimality or maximality criterion. There are di erent views on what an explanation is. One view is that a formula explains an observation i it logically entails this observation. A more correct view is that an explanation gives a cause for the observation [19]. For example, the street is wet may logically entail that it has rained but is not a cause for it and it would be unnatural to de ne the rst as an abductive explanation for the second. Another more illustrative example is cited from [42] the disease paresis is caused by a latent untreated form ....

J.R. Josephson and S.G. Josephson, editors. Abductive Inference: Computation, Philosophy, Technology. New York: Cambridge University Press, 1994.

....processed and reasoned with. Once the knowledge representation is captured, inferences can be made. Inferences can be of several types including prediction and explanation. Prediction is concerned with extending forward from the known past and present to the unknown future (statistical syllogism [15]) Explanation involves the determination of causality by extending from known data back to hypotheses (abduction) 15] 1.2 The Problem Complex systems consist of collections of interacting processes. These processes change over time in response to both internal and external stimuli as well as ....

....of several types including prediction and explanation. Prediction is concerned with extending forward from the known past and present to the unknown future (statistical syllogism [15] Explanation involves the determination of causality by extending from known data back to hypotheses (abduction) [15]. 1.2 The Problem Complex systems consist of collections of interacting processes. These processes change over time in response to both internal and external stimuli as well as to the passage of time itself. There is great variety in the behavior of processes. Some processes are simple events ....

Josephson, John R. and Susan G. Josephson. Abductive Inference: Computation, Philosophy, Technology . Cambridge University Press, 1994.

....represented expectations to inform low level perceptual mechanisms when we consider that one of the chief attractions of an abductive treatment is that it is expressed in high level, declarative terms. For another attempt to reconcile abduction with top down perceptual processing, see [Josephson Josephson, 1994], Chapter 10. To see how this situation might be remedied, let s consider a motivating example. The image at the top of Figure 1 is the output from one of the stereoscopic cameras mounted on the head of an upper torso humanoid robot. The image at the bottom shows the result of applying a ....

....features such as lines, which in turn will be interpreted in terms of surfaces, which are finally interpreted in terms of solid shapes. However, in the formal account that follows, these will be compressed into a single layer. The generalisation to multiple layers is straightforward. See [Josephson Josephson, 1994], Chapter 10 for an abductive account of layered perception. In the following account, we suppose the presence of a mass of sensor data. The focus here is visual perception, and the mass of data in question is taken to be the set of edges detected in a single snapshot of the visual field. ....

J.R.Jospehson and S.G.Josephson, Abductive Inference: Computation, Philosophy, Technology, Cambridge University Press, 1994.

....The term abduction was introduced by the logician and philosopher C.S. Pierce (1839 1914) who de ned it as the inference process of forming a hypothesis that explains given observed phenomena [66] Often abduction has been de ned broadly as any form of inference to the best explanation [40] where best refers to the fact that the generated hypothesis is subjected to extra quality conditions such as (a form of) minimality or some economic criterion. This de nition is extremely general and covers forms of hypothetical reasoning in a wide range of di erent settings, from human scienti c ....

..... 3 Or, more general, if Q and E contain free variables: T j= 8(E Q) 3 an abductive explanation of an observation as a formula which logically entails the observation. However, some have argued, with good reasons, that it is more natural to view an explanation as a cause for the observation [40]. A well known example is as follows [80] the disease paresis is caused by a latent untreated form of syphilis. The probability that latent untreated syphilis leads to paresis is only 25 . Note that in this context, the directionalities of entailment and causality are opposite: syphilis is the ....

J.R. Josephson and S.G. Josephson, editors. Abductive Inference: Computation, Philosophy, Technology. New York: Cambridge University Press, 1994.

....cognitive function, such as explanation or hypothesis generation, while a syllogistic definition 3 This paper will not touch differences between NAL and FOPL that are not directly related to abduction. specifies it as a type of inference step with a specific pattern [Flach and Kakas, 2000; Josephson and Josephson, 1994; Wang, 2000] As shown by the three rule tables, in NAL the distinction among deduction, abduction, and induction is formally specified at the inference step level, according to the position of the shared term (or statement) in the premises. Such a formal definition makes discussions about them ....

....complex cognitive process where multiple types of inference are involved. Therefore, to abstract such a process into a consistent and non trivial pattern is not an easy thing to do, if possible [Wang, 2000] For the same reason, to define abduction as inference toward the best explanation [Josephson and Josephson, 1994] makes things even harder, because besides the derivation of explanations, this definition further requires the evaluation of explanations, and the comparison of competing candidates. In this process, many other factors should be taken into account, such as simplicity, surprising to the system, ....

J. Josephson and S. Josephson, (eds.), Abductive Inference: Computation, Philosophy, Technology. Cambridge University Press, Cambridge, 1994.

.... experience; and they model the selection of the #best explanation as being based solely on likelihood or plausibility, rather than re#ecting the changing needs for information that motivate explanation #Charniak Goldman, 1991; Charniak Shomony, 1994; Hobbs, Stickel, Appelt, Martin, 1993; Josephson Josephson, 1994; Kautz Allen, 1986; Konolige, 1990; Levesque, 1989; O Rorke, 1994; Poole, 1989; Zadrozny, 1994#. Although suchapproaches have proven useful in a number of contexts, problems arise when trying to apply these methods to the rich domain of everyday abductive explanation. Modeling everyday ....

.... in this article is centered on six major issues that arise in the many models of abduction that treat explanations as reasoning chains deriving or supporting belief in a state or event to be explained #Charniak, 1986; Charniak Goldman, 1991; Charniak Shomony, 1994; Hobbs et al. 1993; Josephson Josephson, 1994; Kautz Allen, 1986; Konolige, 1990; Leake, 1992; Levesque, 1989; O Rorke, 1994; Mooney, 1990; Poole, 1989; Wilensky, 1983#. 3 The #rst issue we will address is the nature of explanatory reasoning chains. In many models, these chains are viewed as deductive proofs that may depend on additional ....

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Josephson, J. & Josephson, S. #1994#. Abductive Inference: Computation, Philosophy, Technology. Cambridge University Press, Cambridge, England.

.... yielded several algorithms to compute set covering diagnoses efficiently in practical applications [29,38,44] although this type of diagnostic reasoning is known to be NP hard in general [5] Experimental studies of set covering theory and its variants have been performed by several researchers [21,34,41]. The formal aspects of diagnosis employing causal knowledge have also been studied, using logic as the primary tool [11,13,30,32] In the logical theory of abductive diagnosis, diagnosis is formalized as reasoning from effects to causes, with causal knowledge represented as logical implications ....

J.R. Josephson, S.G. Josephson, Abductive Inference: Computation, Philosophy, Technology, Cambridge University Press, Cambridge, 1994.

.... The Theory of Explanatory Coherence, or TEC, is proposed by Thagard (1989, 1992a) as a model of human abductive reasoning, a process of inference to the best (i.e. most believable) hypothesis or hypotheses that can explain observed data (For general treatments of abduction, see Fann, 1970; Josephson Josephson, 1994). As indicated by its name, TEC takes a coherence view of human belief in general and hypothesis evaluation in particular. According to the theory, it is the coherence based on explanatory relations that is fundamental to human belief evaluation. More specifically, the acceptability of a ....

Josephson, J. R., & Josephson, S. G. (1994). Abductive inference: Computation, philosophy, technology. New York, NY: Cambridge University Press.

.... essential component of many tasks, including medical diagnosis (Feltovich, Johnson, Moller, and Swanson, 1984) scientific discovery (Thagard, 1989) and discourse comprehension (Kintsch, 1988) The key task of abduction is to find a best explanation of a set of observations (Peng Reggia, 1990; Josephson Josephson, 1994). Abduction can be represented in the following general form: The surprising fact C is observed, But if A were true, C would be a matter of course; Hence, there is a reason to suspect that A is true. Clearly, different from deduction, where the conclusion necessarily follows from the premises, ....

....in abduction the conclusion does not follow from the premises with necessity. That is, given a set of observations, many hypotheses (or conjunctive hypotheses) can be formed, each of which may have different degrees of plausibility. In general, how do we select a best one Many researchers (e.g. Josephson Josephson, 1994; Thagard, 1992a; Paul, 1993) distinguish two components of an abductive reasoning process. That is, abduction is a process that includes both hypothesis generation (forming a set of plausible hypotheses) and hypothesis evaluation (choosing a best one) Note that this distinction does not imply ....

Josephson, J.R., & Josephson, S.G. (1994). Abductive Inference: Computation, Philosophy, Technology. Cambridge, NY: Cambridge University Press.

.... consistency based diagnosis traditionally employs a model of normal behaviour, abduction has been the principal model based technique for describing and analysing diagnosis using a model of abnormal behaviour in terms of cause effect relationships [Console et al. 1989; Console Torasso, 1990a; Josephson Josephson, 1994; Reggia et al. 1983; Peng Reggia, 1990; Poole, 1988; Wu, 1991] Early work on abduction has been done by H.E. Pople (cf. Pople, 1973; Pople, 1977] and D. Poole (cf. Poole et al. 1987] Some of the early diagnostic systems that incorporated causal knowledge, such as ABEL and CASNET, are ....

....to formally describe and analyse various notions of diagnosis. The frameworks described in the literature are either logic based (cf. for example [Console et al. 1991] Konolige, 1994] Poole, 1990b; Poole, 1994] and [Ten Teije Van Harmelen, 1994] or based on set theory (cf. for example [Josephson Josephson, 1994] and [Lucas, 1996a] The formalisation of diagnosis is the subject reviewed in this article. The structure of this article is as follows. First, the nature of the diagnostic process is sketched. Next, the various core approaches to diagnosis described in the literature are reviewed. Finally, the ....

[Article contains additional citation context not shown here]

J.R. Josephson and S.G. Josephson (1994). Abductive Inference: Computation, Philosophy, Technology. Cambridge: Cambridge University Press.

.... has yielded several algorithms to compute set covering diagnoses eciently in practical applications [29,38,44] although this type of diagnostic reasoning is known to be NP hard in general [5] Experimental studies of set covering theory and its variants have been performed by several researchers [21,34,41]. The formal aspects of diagnosis employing causal knowledge have also been studied, using logic as the primary tool [11,13,30,32] In the logical theory of abductive diagnosis, diagnosis is formalized as reasoning from e ects to causes, with causal knowledge represented as logical implications of ....

J.R. Josephson and S.G. Josephson, Abductive Inference: Computation, Philosophy, Technology (Cambridge University Press, Cambridge, MA, 1994).

....structural description for an SFF by specifying only a subcomponent s class and parameter range. We need to identify other dimensions along which a component class may be abstracted. The inference strategy implicit in the algorithm described in this thesis is a version of abductive inference [JJ94]. Assuming the given device was designed to achieve specific functions, the task can be viewed as hypothesizing functions of the device that best explain the structural description of the device. Viewed like this the task is a version of abduction problem. Since the primary intention in this ....

John Josephson and Susan Josephson, editors. Abductive Inference: Computation, Philosophy, Technology. Cambridge University Press, 1994. forthcoming.

....term abduction means is the fact that nearly nobody distinguishes clearly between the logical inference and the assessment of its result. This can already be seen from a frequently used characterization of abduction, namely, that it is an inference to the best( explanation (cf. for example, [Josephson and Josephson, 1996] ) That is, not all explanatory inferences (even if their conclusions are only ground formulae, see above) qualify as abductive inferences. To qualify, they must yield a better explanation than all other explanatory inferences (or at least an equally good one) However, it is clear that ....

J. R. Josephson and S. G. Josephson. Abductive Inference --- Computation, Philosophy, Technology. Cambridge University Press, Cambridge, MA, 1996.

....beyond those explicitly modelled by the original designer. Thus, we are not only customizing or extending user interfaces, but actually extending software applications, through intelligent user interfaces. In our approach, end user programming (EUP) mechanisms are cast as abductive processes [14] that operate on figures of speech. Metaphors and metonymies have been chosen because they mirror a natural way of thinking about things we know little or nothing about [15, 16, 17, 21] Compared to alternative approaches that try to meet major EUP cognitive challenges by progressively disclosing ....

Josephson, J.R and Josephson, S.G. (eds.) (1996) Abductive Inference: Computation, Philosophy, Technology. Cambridge University Press.

....entailed. These abducible assumptions are usually in terms of prespecified predicates, called abducibles, which are not (fully) defined in the general theory. In Artificial Intelligence abduction manifests itself as an important form of inference for addressing a variety of problems (e.g. [Poo88, CDT91, KKT93, DS97, Pau93, Ino94, JJ94, Bre96]) These problems include, amongst others, reasoning with incomplete information, updating a database or belief revision and formalizing and addressing application problems like that of planning, diagnosis, natural language understanding and user modeling. Several applications of abduction exist ....

J.R.Josephson and S.G.Josephson. Abductive Inference: Computation, Philosophy, Technology. Cambridge University Press, 1994.

....quality conditions such as (a form of) minimality or maximality criterion. There are different views on what an explanation is. One view is that a formula explains an observation iff it logically entails this observation. A more correct view is that an explanation gives a cause for the observation [17]. For example, the street is wet may logically entail that it has rained but is not a cause for it and it would be unnatural to define the first as an abductive explanation for the second. Another more illustrative example is cited from [37] the disease paresis 1 is caused by a latent untreated ....

J.R. Josephson and S.G. Josephson, editors. Abductive Inference: Computation, Philosophy, Technology. New York: Cambridge University Press, 1994.

....as the model proposed by L. Console and P. Torasso, the pathological behaviour of a biological system is speci ed in terms of cause e ect relationships as discussed in Section 3.2.1. More restrictive models of diagnosis, based on set theory instead of logic, are described in [Peng Reggia, 1990] [Josephson Josephson, 1994] and [Wu, 1991] Diagnostic problem solving is described as the problem of accounting for a given set of observed patient ndings F by supplying the knowledge base KB with a set (conjunction) of hypotheses D which, after computation of the deductive closure, accounts for each of the given ....

....nding in common with the set of observed ndings, may be included in a diagnosis. Above we have discussed deductive and abductive models of diagnosis. Abductive diagnosis has been considered in some detail, because many researchers believe that medical diagnosis is essentially abductive in nature [Josephson Josephson, 1994; Peng Reggia, 1990; Pople, 1973] As we have argued, abductive diagnosis should not be taken as a xed concept. Several di erent notions of abductive diagnosis, based on the nature of the medical domain, can be designed. Both the characteristics of the patient data and the medical knowledge ....

Josephson, JR, and Josephson, SG, 1994. Abductive Inference: Computation,Philosophy, Technology, Cambridge University Press, Cambridge.

....and a user s strategies for assessing relevance [FM95] We view RF as a process of explanation. An RF theory should provide an explanation of why a document is relevant to an information need. These explanations can be based on how information is used within documents. We propose abductive logic, [JJ94] as a suitable framework for an explanation based account of RF. Abductive inference provides hypotheses that explain a given set of data. For example, given that a patient has red spots, an abductive inference engine could provide hypotheses that the patient is suffering from chickenpox, measles ....

J. R. Josephson and S. G. Josephson (ed). Abductive Inference: Computation, Philosophy, Technology. Cambridge University Press. 1994.

.... make the distinction between forming a hypothesis and evaluating and selecting a hypothesis , nowadays, people usually use abduction to refer to the reasoning process that generates a best explanation for a set of observations, thus including both hypothesis generation and hypothesis selection (Josephson Josephson, 1994; Thagard, 1992a; van der Lubbe Backer, 1993) Uncertainty Uncertainty is inevitable at all levels of humans interaction with their environment. At the lowest level, biological processes are never clear cut and without noise. At the perceptual level, people may have difficulty recognizing the ....

Josephson, J.R., & Josephson, S.G. (1994). Abductive Inference: Computation, Philosophy, Technology. Cambridge, NY: Cambridge University Press.

....that would realistically be available in an actual military situation. The situation assessment task is a type of what a type of inference called abductive inference. The analysis in the Appendix is based on the task analysis of abduction in general and situation assessment in particular given in [3]. The task analysis presented in the Appendix will necessarily be very schematic, both because the kind of case studies we have called for have not yet been conducted, and because we give it here with more generality and imprecision than will characterize concrete examples of types of military ....

John R. Josephson and Susan G. Josephson, (Editors), Abductive Inference: Computation, Philosophy, Technology, Cambridge University Press, 1994.

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Josephson, J.R., Josephson, S.J. Abductive Inference: Computation, Philosophy, Technology. New York, Cambridge University Press, (1994).

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Josephson, J. R. and Josephson, S. G. (eds.) Abductive Inference: Computation, Philosophy, Technology. New York: Cambridge University Press. 1994.

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Josephson, J.R., & Josephson, S.G. (1994). Abductive Inference: Computation, Philosophy, Technology. Cambridge, NY: Cambridge University Press.

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