What mechanisms enable artificial systems to understand and actively focus on what is important, to ignore irrelevant detail, and to share attention with humans?

In order to cope with the complexity of natural environments, a key capability of cognitive systems is to rapidly recognize what is relevant and to focus their processing resources accordingly. With regard to human-machine cooperation, the capability to infer and follow the focus of attention of the human user is a basic requirement for efficient team work. In human communication, maintaining a state of shared attention is heavily influenced by emotional and social feedback signals. Modeling similar signals with technical devices, such as animated robot heads, can create a new quality of human-machine interaction. Finally, the deeper understanding of the involved attentional and socio-emotional processes will be of importance to create systems that can exhibit team intelligence.

In order to cope with these questions, CITEC links empirical research including eye-tracking, EEG-analysis and experimental work in the behavioral sciences with engineering approaches. This combination allows the creation of artificial models to gain a better understanding of what is required to build attentive systems that aim to actively align their processing resources with their human partner. A connected goal is to make computers and robots more "social" by developing ways of making the state of such systems intuitively transparent to humans, utilizing natural channels such as facial or prosodic feedback or innovative graphical displays.

Major research foci are the following:

Research Topics

• Micro Attention,
• Focusing on Objects and Events,
• Co-Representation and Joint Attention,
• Cognitive Control.

Coordinators

• Prof. Dr. Thomas Schack
• Prof. Dr. Britta Wrede