Interaction analysis through fuzzy temporal logic: Extensions for clustering and parameter learning
Interaction analysis is defined as the generation of semantic descriptions from machine perception. This can be achieved through a combination of fuzzy metric temporal logic (FMTL) and situation graph trees (SGTs). We extended the FMTL/SGT framework with modules for clustering and parameter learning and we showed their advantages. The contributions of this paper are 1) the combination of FMTL/SGT reasoning with a customized clustering algorithm, 2) a method for learning FMTL rule parameters, 3) a new FMTL/SGT model that implements some powerful fuzzy spatiotemporal concepts, and 4) evaluation of this system in a crisis response control room setting.