For human actors and artificial (either software or embodied sensing) agents that together form an information system, to access, exchange and share knowledge and plans, they have to understand their environment on a mutually comparable (high) level of abstraction. Understanding the environment involves:

• Perception: analyzing of data into information about the elements of the situation (detection, classification, tracking)
• Comprehension: assessing the situation according to some criteria
• Projection: using the situation assessment(s) to predict the future

The goals of the Enhanced Situation Awareness research cluster are to develop techniques for capturing and describing the state of the world at different abstraction levels and to find ways of fusing both historical and current distributed information into meaningful and relevant representations that can be used as a basis for collaborative decision making. The aim is further to develop adaptive learning techniques which are essential to run-time evolution and auto-configuration of decision support systems.

The central questions for the ESA research cluster are:

• How can the information system capture and describe the state of the world by fusing both historical and current distributed information?
• How can the system evolve and adapt itself to a dynamic environment or change in task or goal?