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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 ..."
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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.
Belief revision in probability theory
 InProceedings of the Ninth Conference on Uncertainty in Arti cial Intelligence
, 1993
"... In a probabilitybased reasoning system, Bayes’ theorem and its variations are often used to revise the system’s beliefs. However, if the explicit conditions and the implicit conditions of probability assignments are properly distinguished,it follows that Bayes ’ theorem is not a generally applicabl ..."
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Cited by 21 (17 self)
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In a probabilitybased reasoning system, Bayes’ theorem and its variations are often used to revise the system’s beliefs. However, if the explicit conditions and the implicit conditions of probability assignments are properly distinguished,it follows that Bayes ’ theorem is not a generally applicable revision rule. Upon properly distinguishing belief revision from belief updating, we see that Jeffrey’s rule and its variations are not revision rules, either. Without these distinctions, the limitation of the Bayesian approach is often ignored or underestimated. Revision, in its general form, cannot be done in the Bayesian approach, because a probability distribution function alone does not contain the information needed by the operation. 1
Propagating Imprecise Probabilities In Bayesian Networks
 Artificial Intelligence
, 1996
"... Often experts are incapable of providing `exact' probabilities; likewise, samples on which the probabilities in networks are based must often be small and preliminary. In such cases the probabilities in the networks are imprecise. The imprecision can be handled by secondorder probability distribu ..."
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Cited by 15 (5 self)
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Often experts are incapable of providing `exact' probabilities; likewise, samples on which the probabilities in networks are based must often be small and preliminary. In such cases the probabilities in the networks are imprecise. The imprecision can be handled by secondorder probability distributions. It is convenient to use beta or Dirichlet distributions to express the uncertainty about probabilities. The problem of how to propagate point probabilities in a Bayesian network now is transformed into the problem of how to propagate Dirichlet distributions in Bayesian networks. It is shown that the propagation of Dirichlet distributions in Bayesian networks with incomplete data results in a system of probability mixtures of betabinomial and Dirichlet distributions. Approximate first order probabilities and their second order probability density functions are be obtained by stochastic simulation. A number of properties of the propagation of imprecise probabilities are discuss...
Nonaxiomatic reasoning system (version 2.2
, 1993
"... NonAxiomatic Reasoning System (NARS) is an intelligent reasoning system, where intelligence means working and adapting with insu cient knowledge and resources. NARS uses a new form of term logic, or an extended syllogism, in which several types of uncertainties can be represented and processed, and ..."
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Cited by 13 (11 self)
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NonAxiomatic Reasoning System (NARS) is an intelligent reasoning system, where intelligence means working and adapting with insu cient knowledge and resources. NARS uses a new form of term logic, or an extended syllogism, in which several types of uncertainties can be represented and processed, and in which deduction, induction, abduction, and revision are carried out in a uni ed format. The system works in an asynchronously parallel way. The memory of the system is dynamically organized, and can also be interpreted as a network. After present the major components of the system, its implementation is brie y described. An example is used to show howthe system works. The limitations of the system are also discussed. 1
A Unified Treatment of Uncertainties
 In Proceedings of the Fourth International Conference for Young Computer Scientists
, 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 application environme ..."
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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 an environment, 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. 1 The Problem The central issue of this paper is uncertaint...
A New Approach for Induction: From a NonAxiomatic Logical Point of View
 Philosophy, Logic, and Artificial Intelligence
, 1995
"... NonAxiomatic Reasoning System (NARS) is designed to be a generalpurpose intelligent reasoning system, which is adaptive and works under insufficient knowledge and resources. This paper focuses on the components of NARS that contribute to the system's induction capacity, and shows how the tradition ..."
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Cited by 2 (2 self)
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NonAxiomatic Reasoning System (NARS) is designed to be a generalpurpose intelligent reasoning system, which is adaptive and works under insufficient knowledge and resources. This paper focuses on the components of NARS that contribute to the system's induction capacity, and shows how the traditional problems in induction are addressed by the system. The NARS approach of induction uses an termoriented formal language with an experiencegrounded semantics that consistently interprets various types of uncertainty. An induction rule generates conclusions from common instance of terms, and a revision rule combines evidence from different sources. In NARS, induction and other types of inference, such as deduction and abduction, are based on the same semantic foundation, and they cooperate in inference activities of the system. The system's control mechanism makes knowledgedriven, contextdependent inference possible. 1 Introduction The term "induction" is usually used to denote the infe...
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. ..."
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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...