This paper addresses the problem of situation modeling and machine learning-based decision making in open and non-predictive environments. Situational decision making incorporates the determination of an action based on the current situation, represented by the situation model and trained system behavior using deep neural networks. Commonly, the situation modeling is not considered an intermediate step for decision making in situational action selection. This contribution introduces a novel approach for decision making using situation modeling and deep neural networks. It uses an information structuring and representation technique for the generation of situation spectra used as input to deep learning-based decision making. Simulation-based experimental results show the proposed approach's effectiveness and importance.