IEEE Conference on Cognitive and Computational Aspects of Situation Management
27-31 March 2017 – Savannah, GA

Special Paper Sessions


There will be three special paper sessions planned for the conference.

The Relationships between Situation Awareness, Big Data, and Deep Learning 
Chair: Dr. Mica Endsley, SA Technologies
    • Description: Situation awareness (SA) is the perception of environmental elements and events with respect to time or space, the comprehension of their meaning, and the projection of their status after some variable has changed, such as time, or some other variable, such as a predetermined event (Endsley, 1995). Appropriate SA can directly impact the decision-making process. Previously, achieving situation awareness was easier as decisions were driven by smaller amounts of information. However, data is now created at an expositional rate. More data should mean a reduction in uncertainty and more informed decision making processes. However, access to these data sets alone does not guarantee useful information required for situation management. Exploration of processes related to big data and deep learning could help advance the development of appropriate SA.
    • Possible paper topics include:
      • pattern recognition and data fusion
      • sensor data fusion
      • information fusion
      • machine learning
      • modeling situations
Cognitive Modeling
Chair: Dr. Christian Lebiere, Carnegie Melon University
  • Description: Cognitive models are computational or mathematical representations of the human cognitive processes engaged in perception, cognition and action. Combined with task representations, they provide a quantitative basis for understanding experimental findings in situation awareness and decision making as well as optimizing decision support to the characteristics of the human operator.
  • Possible paper topics include cognitive models of:
    • situation awareness and decision making
    • human interaction with autonomous systems
    • individual differences in situation management
    • human-human and human-agent team interaction
    • model –driven decision-support systems
Interaction with Autonomous Systems
Chair: Dr. Tom Ziemke, Linköping University & University of Skövde, Sweden
  • Description: Human interaction with (partially) autonomous systems (ground, air, surface, or subsurface) is changing as teaming efforts continue to move away from direct control to more intelligent, interdependent collaboration, which poses significant challenges for achieving and maintaining an integrated overall situation awareness. The links between the technological advancements and capabilities in the system design, underlying intelligence architecture, and communication/feedback mechanisms need to be identified and established to facilitate appropriate interaction.
  • Possible paper topics include:
    • Theory, principles, paradigms of human-machine interaction
    • Human-machine collaborative teaming (e.g., trust, SA, transparency, etc.)
    • Dynamic systems and network-centric operations
    • Goal prioritization, and decision-making processes in human-machine systems
    • Intent, communication, and feedback mechanisms
    • System design, algorithms, and architectures
    • Artificial intelligence in interactive autonomous systems
    • Interface technologies and control mechanisms