Consensus measures constructed from aggregation functions and fuzzy implications

We focus on the problem of constructing functions that are able to measure the degree of consensus for a set of inputs provided over the unit interval. When making evaluations based on inputs from multiple criteria, sources or experts, the resulting output can be seen as the value which best represents the individual contributions. However it may also be desirable to know the extent to which the inputs agree. Does the representative value reflect a universal opinion? Or has there been a high degree of tradeoff? We consider the properties relating to such consensus measures and propose two general models built component-wise from aggregation functions and fuzzy implications.