12 Facts About Belief revision

Belief revision is the process of changing beliefs to take into account a new piece of information.

The logical formalization of belief revision is researched in philosophy, in databases, and in artificial intelligence for the design of rational agents.

Main assumption of belief revision is that of minimal change: the knowledge before and after the change should be as similar as possible.

The considered setting is that of Belief revision, that is, different pieces of information referring to the same situation.

Foundationalist revision operators working on non-deductively closed belief sets typically select some subsets of that are consistent with, combined them in some way, and then conjoined them with.

Different realization of the foundational approach to belief revision is based on explicitly declaring the dependences among beliefs.

Specific iterated Belief revision operators have been proposed by Spohn, Boutilier, Williams, Lehmann, and others.

Many Belief revision proposals involve orderings over models representing the relative plausibility of the possible alternatives.

Since a deductively closed knowledge base is infinite, complexity studies on belief revision operators working on deductively closed knowledge bases are done in the assumption that such deductively closed knowledge base are given in the form of an equivalent finite knowledge base.

The Dalal Belief revision is an operator because, once two formulae and are given, no other information is needed to compute.

The complexity for Belief revision schemes is determined in the assumption that the extra information needed to compute Belief revision is given in some compact form.

Belief revision has been used to demonstrate the acknowledgement of intrinsic social capital in closed networks.