Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Uncertain Reasoning Using Maximum Entropy Inference   The use of maximum entropy inference in reasoning with uncertain information
is commonly justified by an information-theoretic argument. This paper
discusses a possible objection to this information-theoretic justification and
shows how it can be met. I then compare maximum entropy inference with certain
other currently popular methods for uncertain reasoning. In making such a
comparison, one must distinguish between static and dynamic theories of degrees
of belief: a static theory concerns the consistency conditions for degrees of
belief at a given time; whereas a dynamic theory concerns how one's degrees of
belief should change in the light of new information. It is argued that maximum
entropy is a dynamic theory and that a complete theory of uncertain reasoning
can be gotten by combining maximum entropy inference with probability theory,
which is a static theory. This total theory, I argue, is much better grounded
than are other theories of uncertain reasoning.

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The categories of this paper are: cmp-lg
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The categories of this paper are: acc-phys
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The categories of this paper are: nucl-th
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The categories of this paper are: chao-dyn
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The categories of this paper are: supr-con
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The categories of this paper are: q-fin
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The categories of this paper are: adap-org
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The categories of this paper are: comp-gas
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The categories of this paper are: eess
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The categories of this paper are: solv-int
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The categories of this paper are: atom-ph
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The categories of this paper are: econ
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The categories of this paper are: hep-lat
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The categories of this paper are: ao-sci
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The categories of this paper are: physics
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The categories of this paper are: dg-ga