Rough Sets in Perception-Based Computing Extended Abstract

Intelligent systems for many real life problems can be modeled by systems of complex objects and their parts changing and interacting over time. The ob-jects are usually linked by certain dependencies, can cooperate between them-selves and are able to perform complex and flexible actions (operations) in an autonomous manner. Such systems are identified as complex dynamical systems [2,40], autonomous multiagent systems [20,40], or swarm intelligent systems (see, e.g., [28,7]). One of the main challenges to be solved in intelligent systems research is the development of methods for approximate reasoning from measurements to perception, i.e., from concepts that can be directly approximated using sensor measurements to concepts, expressed by human beings in natural language, that are the perception results [42]. The existing methodologies and technologies are not adequate to solve many problems associated with this challenge. Among such problems are, e.g., classifi-cation and understanding of medical images [30], control of autonomous system