The starting point of this research is the multimodal approach to modeling multiagent systems, especially Beliefs, Goals and Intention systems. Such an approach is suitable for specifying and verifying many subtle aspects of agents’ informational and motivational attitudes.
However, in this chapter we make a shift in a perspective. More precisely, we propose the method of embedding multimodal approaches into a form of approximate reasoning suitable for modeling perception, namely a similarity-based approximate reasoning. We argue that this formalism allows one to both keep the intuitive semantics compatible with that of multimodal logics as well as to model and implement phenomena occurring at the perception level.