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1. |
Constructive belief and rational representation |
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Computational Intelligence,
Volume 5,
Issue 1,
1989,
Page 1-11
Jon Doyle,
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摘要:
It is commonplace in artificial intelligence to divide an agent's explicit beliefs into two parts: the beliefs explicitly represented ormanifestin memory, and the implicitly represented orconstructivebeliefs that are repeatedly reconstructed when needed rather than memorized. Many theories of knowledge view the relation between manifest and constructive beliefs as a logical relation, with the manifest beliefs representing the constructive beliefs through a logic of belief. This view, however, limits the ability of a theory to treat incomplete or inconsistent sets of beliefs in useful ways. We argue that a more illuminating view is that belief is the result ofrational representation.In this theory, the agent obtains its constructive beliefs by using its manifest beliefs and preferences to rationally (in the sense of decision theory) choose the most useful conclusions indicated by the manifest beliefs.
ISSN:0824-7935
DOI:10.1111/j.1467-8640.1989.tb00311.x
出版商:Blackwell Publishing Ltd
年代:1989
数据来源: WILEY
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2. |
Compiling general linear recursions by variable connection graph analysis |
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Computational Intelligence,
Volume 5,
Issue 1,
1989,
Page 12-31
Jiawei Han,
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摘要:
Compilation is a powerful preprocessing technique in the processing of recursions in knowledge‐based systems. This paper develops a method of compiling and optimizing complex function‐free linear recursions using a variable connection graph, the V‐graph. It shows that a function‐free recursion consisting of a linear recursive rule and one or more nonrecursive rules can be compiled to (1) a bounded recursion, in which recursion can be eliminated from the program, or (2) ann‐chain recursion, whose compiled formula consists of one chain, whenn= 1, ornsynchronized compiled chains, whenn>1. The study is based on a classification of linear recursions and a study of the compilation results of each class. Using the variable connection graph, linear recursions are classified into six classes: acyclic paths, unit cycles, uniform cycles, nonuniform cycles, connected components, and their disjoint mixtures. Recursions in each class share some common properties in compilation. Our study presents an organized picture for the compilation of general function‐free linear recursions. After compilation, the processing of complex linear recursions becomes essentially the processing of primitiven‐chain recursions or bounded recursions to which efficient processing methods
ISSN:0824-7935
DOI:10.1111/j.1467-8640.1989.tb00312.x
出版商:Blackwell Publishing Ltd
年代:1989
数据来源: WILEY
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3. |
Representing defaults with epistemic concepts |
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Computational Intelligence,
Volume 5,
Issue 1,
1989,
Page 32-44
Kurt Konolige,
Karen Myers,
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摘要:
Reasoning about defaults—implications that typically hold, but which may have exceptions—is an important part of commonsense reasoning. We present some parts of a theory of defaults, concentrating on distinctions between various subtle ways in which defaults can be defeated, and on inferences which seem plausible but which are not correct in all cases. To represent this theory in a formal system, it is natural to use the epistemic concept of self‐belief. We show how to express the theory by a local translation into autoepistemic logic, which contains the requisite epistemic oper
ISSN:0824-7935
DOI:10.1111/j.1467-8640.1989.tb00313.x
出版商:Blackwell Publishing Ltd
年代:1989
数据来源: WILEY
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4. |
Learning and classification of monotonic ordinal concepts |
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Computational Intelligence,
Volume 5,
Issue 1,
1989,
Page 45-49
Arie Ben‐David,
Leon Sterling,
Yoh‐Han Pao,
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PDF (591KB)
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摘要:
Ordinal reasoning plays a major role in human cognition. This paper identifies an important class of classification problems of patterns taken from ordinal domains and presents efficient, incremental algorithms for learning the classification rules from examples. We show that by adopting a monotonicity assumption of the output with respect to the input, inconsistencies among examples can be easily detected and the number of possible classification rules substantially reduced. By adopting a conservative classification criterion, the required number of rules further decreases. The monotonicity and conservatism of the classification also enable the resolution of conflicts among inconsistent examples and the graceful handling ofdon't knowsanddon't caresduring the learning and classification phases. Two typical examples in which the suggested classification model works well are given. The first example is taken from the financial domain and the second from machining.
ISSN:0824-7935
DOI:10.1111/j.1467-8640.1989.tb00314.x
出版商:Blackwell Publishing Ltd
年代:1989
数据来源: WILEY
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