Minds and Machines

, Volume 22, Issue 4, pp 325-351

First online:

Probabilistic Belief Contraction

  • Raghav RamachandranAffiliated withDepartment of Computing, Macquarie University Email author 
  • , Arthur RamerAffiliated withSchool of Computer Science and Engineering, University of New South Wales
  • , Abhaya C. NayakAffiliated withDepartment of Computing, Macquarie University

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Probabilistic belief contraction has been a much neglected topic in the field of probabilistic reasoning. This is due to the difficulty in establishing a reasonable reversal of the effect of Bayesian conditionalization on a probabilistic distribution. We show that indifferent contraction, a solution proposed by Ramer to this problem through a judicious use of the principle of maximum entropy, is a probabilistic version of a full meet contraction. We then propose variations of indifferent contraction, using both the Shannon entropy measure as well as the Hartley entropy measure, with an aim to avoid excessive loss of beliefs that full meet contraction entails.


Probabilistic belief change Belief contraction Partial meet contraction Principle of maximum entropy Shannon entropy Hartley entropy