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H. D. Saltzstein and T. Kasachkoff (2004) (see record 2004-21519-004) critique the social intuitionist model (J. Haidt, 2001) (see record 2001-18918-008), but the model they critique is a stripped-down version that should be called the "possum" model. They make 3 charges about the possum model that are not true about the social intuitionist model: that it includes no role for reasoning, that it reduces social influence to compliance, and that it does not take a developmental perspective. After a defense of the honor of the social intuitionist model, this article raises 2 areas of legitimate dispute: the scope and nature of moral reasoning and the usefulness of appealing to innate ideas, rather than to learning and reasoning, as the origin of moral knowledge. This article presents 3 clusters of innate moral intuitions, related to sympathy, hierarchy, and reciprocity. (PsycINFO Database Record (c) 2010 APA, all rights reserved) 相似文献
3.
Inaki Arrazola Agn s Plainfoss Henri Prade Claudette Testemale 《Information Systems》1989,14(6):487-492
This paper presents different approaches which enable a data base management system to obtain a plausible fuzzy estimate for an attribute value of an item for which the information is not explicitly stored in the data base. This can be made either by a kind of analogical reasoning from information about particular items or by means of expert rules which specify the (fuzzy) sets of possible values of the attribute under consideration, for various classes of items. Another kind of expert rules enables the system to compute an estimate from the attribute value of another item provided that, in other respects, this latter item sufficiently resembles the item, the value of which we are interested in; then these expert rules are used either for controlling the analogical reasoning process or for enlarging the scope of application of the first kind of expert rules. The different approaches are discussed in the framework of possibility theory. 相似文献
4.
Maria Zemankova 《Information Systems》1989,14(6):473-486
FILIP (fuzzy intelligent learning information processing) system is designed with the goal to model human information processing. The issues addressed are uncertain knowledge representation and approximate reasoning based on fuzzy set theory, and knowledge acquisition by “being told” or by “learning from examples”. Concepts that can be “learned” by the system can be imprecise (fuzzy), or the knowledge can be incomplete. In the latter case, FILIP uses the concept of similarity to extrapolate the knowledge to cases that were not covered by examples provided by the user. Concepts are stored in the Knowledge Base and employed in intelligent query processing, based on flexible inference that supports approximate matches between the data in the database and the query.
The architecture of FILIP is discussed, the learning algorithm is described, and examples of the system's performance in the knowledge acquisition and querying modes, together with its explanatory capabilities are shown. 相似文献
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We study the computational complexity of the qualitative algebra which is a temporal constraint formalism that combines the point algebra, the point-interval algebra and Allen's interval algebra. We identify all tractable fragments and show that every other fragment is NP-complete. 相似文献
8.
Axel Wabenhorst 《Theoretical computer science》2003,300(1-3):181-207
The Timed Interval Calculus, a timed-trace formalism based on set theory, is introduced. It is extended with an induction law and a unit for concatenation, which facilitates the proof of properties over trace histories. The effectiveness of the extended Timed Interval Calculus is demonstrated via a benchmark case study, the mine pump. Specifically, a safety property relating to the operation of a mine shaft is proved, based on an implementation of the mine pump and assumptions about the environment of the mine. 相似文献
9.
Common sense sometimes predicts events to be likely or unlikely rather than merely possible. We extend methods of qualitative reasoning to predict the relative likelihoods of possible qualitative behaviors by viewing the dynamics of a system as a Markov chain over its transition graph. This involves adding qualitative or quantitative estimates of transition probabilities to each of the transitions and applying the standard theory of Markov chains to distinguish persistent states from transient states and to calculate recurrence times, settling times, and probabilities for ending up in each state. Much of the analysis depends solely on qualitative estimates of transition probabilities, which follow directly from theoretical considerations and which lead to qualitative predictions about entire classes of systems. Quantitative estimates for specific systems are derived empirically and lead to qualitative and quantitative conclusions, most of which are insensitive to small perturbations in the estimated transition probabilities. The algorithms are straightforward and efficient. 相似文献
10.
Dragan Simić Svetlana Simić 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2007,11(12):1185-1192
A concept of business intelligent system for financial prediction is considered in this paper. It provides data needed for
fast, precise and good business decision support to all levels of management. The aim of the project is the development of
a new online analytical processing oriented on case-based reasoning (CBR) where a previous experience for every new problem
is taken into account. Methodological aspects have been tested in practice as a part of the management information system
development project of “Novi Sad Fair”. A case study of an improved application of CBR in prediction of future payments is
discussed in the paper.
This paper is originally presented at The International Conference on Hybrid Information Technology 2006, at the special session
on “Intelligent Information Systems for Financial Engineering”, November 2006 in Cheju Island, Korea. 相似文献