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In our time it is important to solve optimization problems which get the needed data only over time. This thesis provides a framework to learn optimization algorithms just from a problem formulation without additional knowledge but with room to improve is more structure of the problem at hand is provided. Central points of this work are how structure can be defined and how to measure performance of learned algorithms.