IEICE TRANSACTIONS on transactions
Applications of Information Theory into Predicate Logic for AI Systems
Summary :
By considering an analogy between information theory and predicate logic in artificial intelligence (AI) systems, we obtain interesting results in the field of both AI and information theory. First, we define the self-information and the entropy of formulas in predicate logic. Since inference of logic is regarded as information transformation, the information structure of logic is clarified by using mutual information based on the analogy with source coding. Next, we introduce a new concept of hierarchy of information, which have not been very clear in information theory, to discuss the similarity between inference and source coding. Finally, a new theoretical method is proposed for processing uncertain knowledge which can not be treated by the ordinary logic from the foregoing information theoretical concepts.
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- IEICE TRANSACTIONS on transactions Vol.E72-E No.5 pp.443-451
- Publication Date
- 1989/05/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section INVITED PAPER (Special Issue on Information Theory and Its Applications)
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Toshiyasu MATSUSHIMA, Shigeichi HIRASAWA, "Applications of Information Theory into Predicate Logic for AI Systems" in IEICE TRANSACTIONS on transactions,
vol. E72-E, no. 5, pp. 443-451, May 1989, doi: .
Abstract: By considering an analogy between information theory and predicate logic in artificial intelligence (AI) systems, we obtain interesting results in the field of both AI and information theory. First, we define the self-information and the entropy of formulas in predicate logic. Since inference of logic is regarded as information transformation, the information structure of logic is clarified by using mutual information based on the analogy with source coding. Next, we introduce a new concept of hierarchy of information, which have not been very clear in information theory, to discuss the similarity between inference and source coding. Finally, a new theoretical method is proposed for processing uncertain knowledge which can not be treated by the ordinary logic from the foregoing information theoretical concepts.
URL: https://global.ieice.org/en_transactions/transactions/10.1587/e72-e_5_443/_p
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@ARTICLE{e72-e_5_443,
author={Toshiyasu MATSUSHIMA, Shigeichi HIRASAWA, },
journal={IEICE TRANSACTIONS on transactions},
title={Applications of Information Theory into Predicate Logic for AI Systems},
year={1989},
volume={E72-E},
number={5},
pages={443-451},
abstract={By considering an analogy between information theory and predicate logic in artificial intelligence (AI) systems, we obtain interesting results in the field of both AI and information theory. First, we define the self-information and the entropy of formulas in predicate logic. Since inference of logic is regarded as information transformation, the information structure of logic is clarified by using mutual information based on the analogy with source coding. Next, we introduce a new concept of hierarchy of information, which have not been very clear in information theory, to discuss the similarity between inference and source coding. Finally, a new theoretical method is proposed for processing uncertain knowledge which can not be treated by the ordinary logic from the foregoing information theoretical concepts.},
keywords={},
doi={},
ISSN={},
month={May},}
Copy
TY - JOUR
TI - Applications of Information Theory into Predicate Logic for AI Systems
T2 - IEICE TRANSACTIONS on transactions
SP - 443
EP - 451
AU - Toshiyasu MATSUSHIMA
AU - Shigeichi HIRASAWA
PY - 1989
DO -
JO - IEICE TRANSACTIONS on transactions
SN -
VL - E72-E
IS - 5
JA - IEICE TRANSACTIONS on transactions
Y1 - May 1989
AB - By considering an analogy between information theory and predicate logic in artificial intelligence (AI) systems, we obtain interesting results in the field of both AI and information theory. First, we define the self-information and the entropy of formulas in predicate logic. Since inference of logic is regarded as information transformation, the information structure of logic is clarified by using mutual information based on the analogy with source coding. Next, we introduce a new concept of hierarchy of information, which have not been very clear in information theory, to discuss the similarity between inference and source coding. Finally, a new theoretical method is proposed for processing uncertain knowledge which can not be treated by the ordinary logic from the foregoing information theoretical concepts.
ER -
English
