Sentence examples for minimal inconsistency from inspiring English sources

We find the minimal inconsistency cover set is the minimal number of policies that represent a policy inconsistency.

Firstly, we reduce the complexity of reasoning about policy inconsistencies by static pruning technique and minimal inconsistency cover set.

We define a minimal inconsistency cover (MIC) set responsible for a policy inconsistency that includes the smallest number of policies.

Thus we reduce the complexity of reasoning about policy inconsistencies by the techniques of static pruning and minimal inconsistency cover set.

We compute the minimal inconsistency cover set that is responsible for the policy inconsistencies; thus we only need to examine the minimum number of policies.

However, as illustrated by the well-known Lottery Paradox, as the size of a minimal inconsistent subset increases, the degree of its inconsistency decreases.

Finally, we show how inconsistency measures based on hitting sets of minimal inconsistent sets can be extended using hitting sets of DMUSes.

However, consistent subsets of a belief base also have an impact on the syntax sensitive normalized measures of the degree of inconsistency, the reason for this is that each consistent subset can be considered as a distinctive plausible perspective reflected by that belief base, whilst each minimal inconsistent subset projects a distinctive view of the inconsistency.

Minimal inconsistent sets have been the main tool to localise inconsistency, but we argue that they are like the exposed part of an iceberg, failing to capture contradictions hidden under the water.

It has been increasingly recognized that deriving syntax sensitive inconsistency measures for a belief base from its minimal inconsistent subsets is a natural way forward.

To address these two issues, we propose a normalized framework for measuring the degree of inconsistency of a belief base which unifies the impact of both consistent subsets and minimal inconsistent subsets.