Redundant knowledge map

Two disconnected knowledge maps, K₁ and K₂, constitute a redundant knowledge map, K_R, when:

a) a barren node, B₁, in K₁ corresponds exactly to a barren node, B₂, in K₂ (ie, nodes B₁ and B₂ represent exactly the same distinction);

b) the probability distributions of B₁ and B₂ are assessed, respectively, in the context of K₁ and K₂ without regard for the other knowledge map.

A redundant knowledge map can be very helpful in assessing a probability distribution for a given uncertain variable, U, from various different perspectives. At least initially, these perspectives may yield quite different probability distributions for U—further adjustments may subsequently be made to arrive at a consistent final assessment.

See also: expert.