Unification of Epistemic and Ontic Concepts of Information, Probability, and Entropy, Using Cognizers-System Model
Information and probability are common words used in scientific investigations. However, information and probability both involve epistemic (subjective) and ontic (objective) interpretations under the same terms, which causes controversy within the concept of entropy in physics and biology. There is...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-02-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/21/2/216 |
| _version_ | 1817996714736353280 |
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| author | Toshiyuki Nakajima |
| author_facet | Toshiyuki Nakajima |
| author_sort | Toshiyuki Nakajima |
| collection | DOAJ |
| description | Information and probability are common words used in scientific investigations. However, information and probability both involve epistemic (subjective) and ontic (objective) interpretations under the same terms, which causes controversy within the concept of entropy in physics and biology. There is another issue regarding the circularity between information (or data) and reality: The observation of reality produces phenomena (or events), whereas the reality is confirmed (or constituted) by phenomena. The ordinary concept of information presupposes reality as a source of information, whereas another type of information (known as <i>it-from-bit</i>) constitutes the reality from data (bits). In this paper, a monistic model, called the cognizers-system model (CS model), is employed to resolve these issues. In the CS model, observations (epistemic) and physical changes (ontic) are both unified as “cognition„, meaning a related state change. Information and probability, epistemic and ontic, are formalized and analyzed systematically using a common theoretical framework of the CS model or a related model. Based on the results, a perspective for resolving controversial issues of entropy originating from information and probability is presented. |
| first_indexed | 2024-04-14T02:26:19Z |
| format | Article |
| id | doaj.art-361ac908e6274db68c298767035f0e79 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-14T02:26:19Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-361ac908e6274db68c298767035f0e792022-12-22T02:17:52ZengMDPI AGEntropy1099-43002019-02-0121221610.3390/e21020216e21020216Unification of Epistemic and Ontic Concepts of Information, Probability, and Entropy, Using Cognizers-System ModelToshiyuki Nakajima0Department of Biology, Ehime University, Ehime Prefecture 790-8577, JapanInformation and probability are common words used in scientific investigations. However, information and probability both involve epistemic (subjective) and ontic (objective) interpretations under the same terms, which causes controversy within the concept of entropy in physics and biology. There is another issue regarding the circularity between information (or data) and reality: The observation of reality produces phenomena (or events), whereas the reality is confirmed (or constituted) by phenomena. The ordinary concept of information presupposes reality as a source of information, whereas another type of information (known as <i>it-from-bit</i>) constitutes the reality from data (bits). In this paper, a monistic model, called the cognizers-system model (CS model), is employed to resolve these issues. In the CS model, observations (epistemic) and physical changes (ontic) are both unified as “cognition„, meaning a related state change. Information and probability, epistemic and ontic, are formalized and analyzed systematically using a common theoretical framework of the CS model or a related model. Based on the results, a perspective for resolving controversial issues of entropy originating from information and probability is presented.https://www.mdpi.com/1099-4300/21/2/216cognitioncognizers systeminformationprobabilityentropyobserverobservation(un)certaintyrelative frequency |
| spellingShingle | Toshiyuki Nakajima Unification of Epistemic and Ontic Concepts of Information, Probability, and Entropy, Using Cognizers-System Model Entropy cognition cognizers system information probability entropy observer observation (un)certainty relative frequency |
| title | Unification of Epistemic and Ontic Concepts of Information, Probability, and Entropy, Using Cognizers-System Model |
| title_full | Unification of Epistemic and Ontic Concepts of Information, Probability, and Entropy, Using Cognizers-System Model |
| title_fullStr | Unification of Epistemic and Ontic Concepts of Information, Probability, and Entropy, Using Cognizers-System Model |
| title_full_unstemmed | Unification of Epistemic and Ontic Concepts of Information, Probability, and Entropy, Using Cognizers-System Model |
| title_short | Unification of Epistemic and Ontic Concepts of Information, Probability, and Entropy, Using Cognizers-System Model |
| title_sort | unification of epistemic and ontic concepts of information probability and entropy using cognizers system model |
| topic | cognition cognizers system information probability entropy observer observation (un)certainty relative frequency |
| url | https://www.mdpi.com/1099-4300/21/2/216 |
| work_keys_str_mv | AT toshiyukinakajima unificationofepistemicandonticconceptsofinformationprobabilityandentropyusingcognizerssystemmodel |