Maximum Entropy and Probability Kinematics Constrained by Conditionals

Entropy

Stefan Lukits¹  Juergen Landes¹ 

[1] Philosophy Department, University of British Columbia, 1866 Main Mall, Buchanan E370, Vancouver BC V6T 1Z1, Canada; E-Mail

关键词: probability update;    Jeffrey conditioning;    principle of maximum entropy;    formal epistemology;    conditionals;    probability kinematics;   

DOI  :  10.3390/e17041690

来源: mdpi

【 摘 要 】

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) is Wagner 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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland