Qualitative Reasoning (QR)
Qualitative Reasoning (QR) is a research area at the interface of Artificial Intelligence, Cognitive Science, Engineering, and Science. Its core objective is to model real world systems that have continuous aspects about which we only have incomplete or qualitative knowledge. In seeking to understand human ability to reason qualitatively, QR combines the quest for comprehension of effective reasoning about systems and new ways to supplement conventional modeling, analysis, diagnosis, and control techniques to tackle real-world applications.
Humans are capable of intelligently action in complex environments. For instance, humans can find their destination in a city, interact with other people to exchange information or to arrange objects in a room in a suitable way. In these tasks, humans outperform current technical systems such as autonomous robots. Research in cognitive systems aims to: (a) gain a deeper understanding of how humans realise their unique intelligent potential; (b) develop artificial cognitive agents to assist humans in performing demanding tasks in order to strengthen their autonomy.
Qualitative Reasoning for Cognitive Assistance Systems
QR-2013 especially welcomes perspectives that emphasise the development of systematic human-centred models and methods for commonsense qualitative reasoning that may be seamlessly integrated within larger artificial intelligence projects, cognitive (assistance) systems, industrial automation systems, and hybrid intelligent systems.
Human-like commonsense qualitative reasoning promises to become a fundamental aspect of cognitive assistance systems that will accompany us in daily personal and professional activities. Such reasoning could pertain to everyday activities and even specialist problem-solving concerning phenomena that involve, e.g., creativity, complex data understanding, interpretation of people interactions, real-time situational awareness etc.
Formal representational and computational methods for handling commonsense qualitative phenomena - e.g., involving the perception of space, time, events, actions, change, causality, processes - will be at the heart of collaborative cognitive systems and assistive technologies with specialized capabilities that aid humans in creative and productive tasks, knowledge discovery and data analytics, high-level control of autonomous systems etc.