Probabilistic logic in computer science
| Autor: | S. V. Bulgakov, I. I. Lonsky, V. Ya. Tsvetkov |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
business.industry
Computer science Generalization Probabilistic logic Logical modeling Connection (mathematics) TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES Information model Computer Science::Logic in Computer Science Entropy (information theory) Logical data model Artificial intelligence business Hardware_LOGICDESIGN |
| Zdroj: | AIP Conference Proceedings. |
| ISSN: | 0094-243X |
| DOI: | 10.1063/5.0071597 |
| Popis: | The article examines probabilistic logic as applied to computer science and its problems. Probabilistic logic is treated as a generalization of formal logic. In many cases, the application of probabilistic logic occurs under conditions of uncertainty. Probabilistic logic uses a model approach. Computer science also uses a model approach. Probabilistic logic describes uncertainty using quantitative values of probability. Computer science describes uncertainty using the concept of information entropy. The article introduces the concept of informational logical uncertainty. The article finds a connection between probabilistic logic and entropy. This connection makes it possible to build a probabilistically logical model. This connection makes it possible to create probabilistically logical modeling, which is in many ways an analogue of information modeling. The purpose of probabilistically logical modeling is to overcome information and logical uncertainty. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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