10.18453/rosdok_id00002533 Nyolt, Martin Martin Nyolt http://d-nb.info/gnd/1196553475 Universität Rostock 2019 004 Data processing Computer sciences 2019 en http://purl.uni-rostock.de/rosdok/id00002533 urn:nbn:de:gbv:28-rosdok_id00002533-3 This dissertation analyses these challenges and provides solutions for SMC methods. The large, categorical and causal state-space is the largest factor for the inefficiency of current SMC methods. The marginal filter is analysed in detail for its advantages in categorical states over the particle filter. An optimal pruning strategy for the marginal filter is derived that limits the number of samples.