TY  - BOOK
AU  - Lüdtke, Stefan
PY  - 2020
DA  - 2020//
TI  - Lifted Bayesian filtering in multi-entity systems
PB  - Universität Rostock
CY  - Rostock
AB  - This thesis focuses on Bayesian filtering for systems that consist of multiple, interacting entites (e.g. agents or objects), which can naturally be described by Multiset Rewriting Systems (MRSs). The main insight is that the state space that is underling an MRS exhibits a certain symmetry, which can be exploited to increase inference efficiency. We provide an efficient, lifted filtering algorithm, which is able to achieve a factorial reduction in space and time complexity, compared to conventional, ground filtering.<eng>
UR  - http://purl.uni-rostock.de/rosdok/id00003022
UR  - https://nbn-resolving.org/urn:nbn:de:gbv:28-rosdok_id00003022-4
UR  - https://d-nb.info/1293663522/34
UR  - https://doi.org/10.18453/rosdok_id00003022
DO  - 10.18453/rosdok_id00003022
LA  - English
N1  - vorgelegt von Stefan Lüdtke
ID  - 1757652698
ER  -