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From inheritance relation to nonaxiomatic logic
 International Journal of Approximate Reasoning
, 1994
"... NonAxiomatic Reasoning System is an adaptive system that works with insu cient knowledge and resources. At the beginning of the paper, three binary term logics are de ned. The rst is based only on an inheritance relation. The second and the third suggest a novel way to process extension and intensi ..."
Abstract

Cited by 33 (25 self)
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NonAxiomatic Reasoning System is an adaptive system that works with insu cient knowledge and resources. At the beginning of the paper, three binary term logics are de ned. The rst is based only on an inheritance relation. The second and the third suggest a novel way to process extension and intension, and they also have interesting relations with Aristotle's syllogistic logic. Based on the three simple systems, a NonAxiomatic Logic is de ned. It has a termoriented language and an experiencegrounded semantics. It can uniformly represents and processes randomness, fuzziness, and ignorance. It can also uniformly carries out deduction, abduction, induction, and revision.
Confidence as HigherOrder Uncertainty
, 2001
"... With conicting evidence, a reasoning system derives uncertain conclusions. If the system is open to new evidence, it faces additionally a higherorder uncertainty, because the rstorder uncertainty evaluations are uncertain themselves  they can be changed by future evidence. A new measurement, cond ..."
Abstract

Cited by 9 (7 self)
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With conicting evidence, a reasoning system derives uncertain conclusions. If the system is open to new evidence, it faces additionally a higherorder uncertainty, because the rstorder uncertainty evaluations are uncertain themselves  they can be changed by future evidence. A new measurement, condence, is introduced for this higherorder uncertainty. It is de ned in terms of the amount of available evidence, and interpreted and processed as the relative stability of the rstorder uncertainty evaluation. Its relation with other approaches of \reasoning with uncertainty " is also discussed. Keywords. condence, evidence, frequency interval, revision, inference, deduction, induction, abduction. 1
A Unified Treatment of Uncertainties
, 1993
"... "Uncertainty in artificial intelligence" is an active research field, where several approaches have been suggested and studied for dealing with various types of uncertainty. However, it's hard to rank the approaches in general, because each of them is usually aimed at a special applic ..."
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Cited by 3 (3 self)
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"Uncertainty in artificial intelligence" is an active research field, where several approaches have been suggested and studied for dealing with various types of uncertainty. However, it's hard to rank the approaches in general, because each of them is usually aimed at a special application environment. This paper begins by defining such anenvironment, then show why some existing approaches cannot be used in such a situation. Then a new approach, NonAxiomatic Reasoning System, is introduced to work in the environment. The system is designed under the assumption that the system's knowledge and resources are usually insufficient to handle the tasks imposed by its environment. The system can consistently represent several types of uncertainty, and can carry out multiple operations on these uncertainties. Finally, the new approach is compared with the previous approaches in terms of uncertainty representation and interpretation.
Confidence as Higher Order Uncertainty
"... With insufficient knowledge, the conclusions made by a reasoning system are usually uncertain. If the system is open to new knowledge, it also suffers from a higher order uncertainty, because the first order uncertainty evaluations are uncertain themselves  they can be changed by future evidence. ..."
Abstract

Cited by 2 (1 self)
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With insufficient knowledge, the conclusions made by a reasoning system are usually uncertain. If the system is open to new knowledge, it also suffers from a higher order uncertainty, because the first order uncertainty evaluations are uncertain themselves  they can be changed by future evidence. Several approaches have been proposed for handling higher order uncertainty, including the Bayesian approach, higherorder probability, and so on. Though each of them has its advantages, none of them is satisfactory, for various reasons. A new measurement, confidence, is defined to indicate higher order uncertainty, which is understood as relative stability of first order uncertainty evaluation, and is processed accordingly. 1 Introduction NonAxiomatic Reasoning System (NARS for short) is an intelligent reasoning system ([20, 21]). As a reasoning system, it accept knowledge from its environment in a formal language, and answer questions according to its knowledge. As an intelligent system...
and
"... Our main result here is the development of a general procedure for transforming some initial probability distribution into a new probability distribution in a way that the resulting distribution has entropy at least as great as the original distribution. A significant aspect of our approach is that ..."
Abstract
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Our main result here is the development of a general procedure for transforming some initial probability distribution into a new probability distribution in a way that the resulting distribution has entropy at least as great as the original distribution. A significant aspect of our approach is that it makes use of the Zadeh's entailment principle which is itself a general procedure for going from an initial possibility distribution to a new possibility distribution so that the resulting possibility has an uncertainty at least as great of the original. 1.
and
"... Our main result here is the development of a general procedure for transforming some initial probability distribution into a new probability distribution in a way that the resulting distribution has entropy at least as great as the original distribution. A significant aspect of our approach is that ..."
Abstract
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Our main result here is the development of a general procedure for transforming some initial probability distribution into a new probability distribution in a way that the resulting distribution has entropy at least as great as the original distribution. A significant aspect of our approach is that it makes use of the Zadeh's entailment principle which is itself a general procedure for going from an initial possibility distribution to a new possibility distribution so that the resulting possibility has an uncertainty at least as great of the original. 1.