Maximum Entropy and Probability Kinematics Constrained by Conditionals
Two open questions of inductive reasoning are solved: (1) does the principle of maximum entropy (PME) give a solution to the obverse Majerník problem; and (2) isWagner correct when he claims that Jeffrey’s updating principle (JUP) contradicts PME? Majerník shows that PME provides unique and plausibl...
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-03-01
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| Series: | Entropy |
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| Online Access: | http://www.mdpi.com/1099-4300/17/4/1690 |
| _version_ | 1798038491706163200 |
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| author | Stefan Lukits |
| author_facet | Stefan Lukits |
| author_sort | Stefan Lukits |
| collection | DOAJ |
| description | Two open questions of inductive reasoning are solved: (1) does the principle of maximum entropy (PME) give a solution to the obverse Majerník problem; and (2) isWagner correct when he claims that Jeffrey’s updating principle (JUP) contradicts PME? Majerník shows that PME provides unique and plausible marginal probabilities, given conditional probabilities. The obverse problem posed here is whether PME also provides such conditional probabilities, given certain marginal probabilities. The theorem developed to solve the obverse Majerník problem demonstrates that in the special case introduced by Wagner PME does not contradict JUP, but elegantly generalizes it and offers a more integrated approach to probability updating. |
| first_indexed | 2024-04-11T21:40:56Z |
| format | Article |
| id | doaj.art-188cc15a90d54b498318c838debecdbf |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-11T21:40:56Z |
| publishDate | 2015-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-188cc15a90d54b498318c838debecdbf2022-12-22T04:01:36ZengMDPI AGEntropy1099-43002015-03-011741690170010.3390/e17041690e17041690Maximum Entropy and Probability Kinematics Constrained by ConditionalsStefan Lukits0Philosophy Department, University of British Columbia, 1866 Main Mall, Buchanan E370, Vancouver BC V6T 1Z1, CanadaTwo open questions of inductive reasoning are solved: (1) does the principle of maximum entropy (PME) give a solution to the obverse Majerník problem; and (2) isWagner correct when he claims that Jeffrey’s updating principle (JUP) contradicts PME? Majerník shows that PME provides unique and plausible marginal probabilities, given conditional probabilities. The obverse problem posed here is whether PME also provides such conditional probabilities, given certain marginal probabilities. The theorem developed to solve the obverse Majerník problem demonstrates that in the special case introduced by Wagner PME does not contradict JUP, but elegantly generalizes it and offers a more integrated approach to probability updating.http://www.mdpi.com/1099-4300/17/4/1690probability updateJeffrey conditioningprinciple of maximum entropyformal epistemologyconditionalsprobability kinematics |
| spellingShingle | Stefan Lukits Maximum Entropy and Probability Kinematics Constrained by Conditionals Entropy probability update Jeffrey conditioning principle of maximum entropy formal epistemology conditionals probability kinematics |
| title | Maximum Entropy and Probability Kinematics Constrained by Conditionals |
| title_full | Maximum Entropy and Probability Kinematics Constrained by Conditionals |
| title_fullStr | Maximum Entropy and Probability Kinematics Constrained by Conditionals |
| title_full_unstemmed | Maximum Entropy and Probability Kinematics Constrained by Conditionals |
| title_short | Maximum Entropy and Probability Kinematics Constrained by Conditionals |
| title_sort | maximum entropy and probability kinematics constrained by conditionals |
| topic | probability update Jeffrey conditioning principle of maximum entropy formal epistemology conditionals probability kinematics |
| url | http://www.mdpi.com/1099-4300/17/4/1690 |
| work_keys_str_mv | AT stefanlukits maximumentropyandprobabilitykinematicsconstrainedbyconditionals |