  Goal-models (GM) have been used in adaptive systems engineering for their
ability to capture the different ways to fulfill the requirements. Contextual
GM (CGM) extend these models with the notion of context and context-dependent
applicability of goals. In this paper, we observe that the interpretation of a
goal achievement is itself context-dependent. Thus, we introduce the notion of
Pragmatic Goals which have a dynamic satisfaction criteria. We also developed
and evaluated an algorithm to decide the Pragmatic CGM's achievability.
Finally, we performed several experiments to evaluate and to compare our
algorithm against human judgment and concluded that the specification of
context-dependent goals' applicability and interpretations make it hard for
domain stakeholders to decide whether the model covers all possibilities, both
in terms of time and accuracy, thus showing the importance and contribution of
our algorithm.
