A method has been developed for generating, refining and determining the consequences of complex systems of multiple cause and effect relationships. The novel method is applicable to biological systems as well as man-made systems, as it is based on the collecting and using observed behaviors as well as previous understood mechanism or relationships. The method is particularly useful in multi-variable system with significant interactions among sub-components, especially when there is limited expertise or complete understanding of all the components and their respective relationships interactions. In these cases the method provides guidance for future experiments that develop further expertise. The method has particular power and benefit as it provides for a distinction and comparison of the merits of conducting further experiments based on defined criteria. For example alternative solutions or experiments can be suggested and distinguished on the basis of cost, delay or a negative or detrimental outcome, based on prior experience and knowledge of interactions, in contrast to those that provide additional insight or solve the problem with a lower risk of negative implications.
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