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A non-monotonic logic is a formal logic whose entailment relation is not monotonic.In other words, non-monotonic logics are devised to capture and represent defeasible inferences, i.e., a kind of inference in which reasoners draw tentative conclusions, enabling reasoners to retract their conclusion(s) based on further evidence. [1]
Default logic is a non-monotonic logic proposed by Raymond Reiter to formalize reasoning with default assumptions.. Default logic can express facts like “by default, something is true”; by contrast, standard logic can only express that something is true or that something is false.
Circumscription is a non-monotonic logic created by John McCarthy to formalize the common sense assumption that things are as expected unless otherwise specified. [1] [2] Circumscription was later used by McCarthy in an attempt to solve the frame problem.
Deductive inference is monotonic: if a conclusion is reached on the basis of a certain set of premises, then that conclusion still holds if more premises are added. By contrast, everyday reasoning is mostly non-monotonic because it involves risk: we jump to conclusions from deductively insufficient premises.
Defeasible logic is a non-monotonic logic proposed by Donald Nute to formalize defeasible reasoning. In defeasible logic, there are three different types of propositions: strict rules specify that a fact is always a consequence of another; defeasible rules specify that a fact is typically a consequence of another; undercutting defeaters
Non-monotonic reasoning. Non-monotonic reasoning allows various kinds of hypothetical reasoning. The system associates facts asserted with the rules and facts used to justify them and as those facts change updates the dependent knowledge as well. In rule based systems this capability is known as a truth maintenance system. [25] Expressive ...
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The rational consequence relation is non-monotonic, and the relation is intended to carry the meaning theta usually implies phi or phi usually follows from theta.In this sense it is more useful for modeling some everyday situations than a monotone consequence relation because the latter relation models facts in a more strict boolean fashion—something either follows under all circumstances or ...