58 resultados para Lessing, Gotthold Ephraim, 1729-1781.

em Greenwich Academic Literature Archive - UK


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HYPERJOSEPH combines hypertext, information retrieval, literary studies, Biblical scholarship, and linguistics. Dialectically, this paper contrasts hypertextual form (the extant tool) and AI-captured content (a desideratum), in the HYPERJOSEPH project. The discussion is more general and oriented to epistemology.

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Argumentation as reflected in a short communication from the published literature of botany and zoology is discussed. Trying to capture the logic structure of the argument, however imperfectly, is relevant to information science and depends on a particular goal: namely, to potentially benefit the task of sketching the relationship between bibliographic entries in a better manner than is possible with present-day bibliometric or scientometric practice. This imposes tight limits on the depth of analysis of the text.

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One thing is (a) to develop a system that handles some task to one's satisfaction, and also has a universally recognized myrthful side to its output. Another thing is (b) to provide an analysis of why you are getting such a byproduct. Yet another thing is (c) to develop a model that incorporates reflection about some phenomenon in humor for its own sake. This paper selects for discussion especially Alibi, going on to describe the preliminaries of Columbus. The former, which fits in (a), is a planner with an explanatory capability. It invents pretexts. It's no legal defense, but it is relevant to evidential thinking in AI & Law. Some of the output pretext are myrthful. Not in the sense they are silly: they are not. A key factor seems to be the very alacrity at explaining out detail after detail of globally damning evidence. I attempt a reanalysis of Alibi in respect of (b). As to Columbus, it fits instead in (c). We introduce here the basics of this (unimplemented) model, developed to account for a sample text in parody.

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FUELCON is an expert system in nuclear engineering. Its task is optimized refueling-design, which is crucial to keep down operation costs at a plant. FUELCON proposes sets of alternative configurations of fuel-allocation; the fuel is positioned in a grid representing the core of a reactor. The practitioner of in-core fuel management uses FUELCON to generate a reasonably good configuration for the situation at hand. The domain expert, on the other hand, resorts to the system to test heuristics and discover new ones, for the task described above. Expert use involves a manual phase of revising the ruleset, based on performance during previous iterations in the same session. This paper is concerned with a new phase: the design of a neural component to carry out the revision automatically. Such an automated revision considers previous performance of the system and uses it for adaptation and learning better rules. The neural component is based on a particular schema for a symbolic to recurrent-analogue bridge, called NIPPL, and on the reinforcement learning of neural networks for the adaptation.

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FUELCON is an expert system for optimized refueling design in nuclear engineering. This task is crucial for keeping down operating costs at a plant without compromising safety. FUELCON proposes sets of alternative configurations of allocation of fuel assemblies that are each positioned in the planar grid of a horizontal section of a reactor core. Results are simulated, and an expert user can also use FUELCON to revise rulesets and improve on his or her heuristics. The successful completion of FUELCON led this research team into undertaking a panoply of sequel projects, of which we provide a meta-architectural comparative formal discussion. In this paper, we demonstrate a novel adaptive technique that learns the optimal allocation heuristic for the various cores. The algorithm is a hybrid of a fine-grained neural network and symbolic computation components. This hybrid architecture is sensitive enough to learn the particular characteristics of the ‘in-core fuel management problem’ at hand, and is powerful enough to use this information fully to automatically revise heuristics, thus improving upon those provided by a human expert.

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The consecutive, partly overlapping emergence of expert systems and then neural computation methods among intelligent technologies, is reflected in the evolving scene of their application to nuclear engineering. This paper provides a bird's eye view of the state of the application in the domain, along with a review of a particular task, the one perhaps economically more important: refueling design in nuclear power reactors.

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We provide a select overview of tools supporting traditional Jewish learning. Then we go on to discuss our own HyperJoseph/HyperIsaac project in instructional hypermedia. Its application is to teaching, teacher training, and self-instruction in given Bible passages. The treatment of two narratives has been developed thus far. The tool enables an analysis of the text in several respects: linguistic, narratological, etc. Moreover, the Scriptures' focality throughout the cultural history makes this domain of application particularly challenging, in that there is a requirement for the tool to encompass the accretion of receptions in the cultural repertoire, i.e., several layers of textual traditions—either hermeneutic (i.e., interpretive), or appropriations—related to the given core passage, thus including "secondary" texts (i.e., such that are responding or derivative) from as disparate realms as Roman-age and later homiletics, Medieval and later commentaries or supercommentaries, literary appropriations, references to the arts and modern scholarship, etc. in particular, the Midrash (homiletic expansions) is adept at narrative gap filling, so the narratives mushroom at the interstices where the primary text is silent. The genealogy of the project is rooted in Weiss' index of novelist Agnon's writings, which was eventually upgraded into a hypertextual tool, including Agnon's full-text and ancillary materials. Those early tools being intended primarily for reference and research-support in literary studies, the Agnon hypertext system was initially emulated in the conception of HyperJoseph, which is applied to the Joseph story from Genesis. Then, the transition from a tool for reference to an instructional tool required a thorough reconception in an educational perspective, which led to HyperIsaac, on the sacrifice of Isaac, and to a redesign and upgrade of HyperJoseph as patterned after HyperIsaac.

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Over a time span of almost a decade, the FUELCON project in nuclear engineering has led to a fully functional expert system and spawned sequel projects. Its task is in-core fuel management, also called `refueling', i.e., good fuel-allocation for reloading the core of a given nuclear reactor, for a given operation cycle. The task is crucial for keeping down operation costs at nuclear power plants. Fuel comes in different types and is positioned in a grid representing the core of a reactor. The tool is useful for practitioners but also helps the expert in the domain to test his or her rules of thumb and to discover new ones.

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Those temporal formalisms that are sporadically found nowadays in the literature of AI & Law are based on temporal logic. We claim a revived role for another major class of temporal representation: Petri nets. This formalism, popular in computing from the 1970s, had its potential recognized on occasion in the literature of legal computing as well, but apparently the discipline has lost sight of it, and its practitioners on average need be tutored into this kind of representation. Asynchronous, concurrent processes—for which the approach is well‐suited—are found in the legal domain, in disparate contexts. We develop an example for Mutual Wills.

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Review of: Rosalind W. Picard, Affective Computing

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This paper describes a knowledge-based temporal representation of state transitions for industrial real-time systems. To allow expression of uncertainty, we shall define fluents as disjuncts of positive/negative time-varying properties. A state of the world is represented as a collection of fluents, which is usually incomplete in the sense that neither the positive form nor the negative form of some properties can be implied from it. The world under consideration is assumed to persist in a given state until an action(s) takes place to effect a transition of it into another state, where actions may either be instantaneous or durative. High-level causal laws are characterized in terms of relationships between actions and the involved world states. An effect completion axiom is imposed on each causal law to guarantee that all the fluents that can be affected by the performance of the corresponding action are governed. This completion requirement is practical for most industrial real-time applications and in fact provides a simple and effective treatment to the so-called frame problem.

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Guest editorial

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Logic-based models are thriving within artificial intelligence. A great number of new logics have been defined, and their theory investigated. Epistemic logics introduce modal operators for knowledge or belief; deontic logics are about norms, and introduce operators of deontic necessity and possibility (i.e., obligation or prohibition). And then we have a much investigated class—temporal logics—to whose application to engineering this special issue is devoted. This kind of formalism deserves increased widespread recognition and application in engineering, a domain where other kinds of temporal models (e.g., Petri nets) are by now a fairly standard part of the modelling toolbox.