Cognitive Situation Management


The Technical Committee on Cognitive Situation Management sees its mission in the following:

  • Creating a rich, diverse and comprehensive scientific research environment for advancing the science, applications, and education in the field of cognitive situation management by fostering inter-disciplinary approaches from computer science, human-centered artificial intelligence, cognitive science, human factors research and other related fields;
  • Organizing scientific conferences, workshops and technical sessions to provide researchers, practitioners and government personnel effective forums for exchanging ideas and result to promote advancements in the field of cognitive situation management;
  • Promoting and supporting publications of research and application papers, dedicated special issues and reports in journals, magazines and in electronic media;
  • Encouraging, advising and educating young researchers in the field of cognitive situation management;
  • Promoting and facilitating inter-disciplinary scientific cooperation with other professional societies and events within IEEE and other international organizations, esp. exploring synergies with other SMCS Technical Committees focusing related research fields or enabling technologies and application areas for Cognitive Situation Management.


In many of today’s dynamic, data-rich domains, characterized by complex interactions between multiple agents (such as traffic control, infrastructure and cybersecurity monitoring, disaster response and crisis management, communications and defense), maintaining situation awareness becomes increasingly challenging for both human and non-human actors. Yet, an agent’s situation awareness represents the foundation for its informed decision making to take the appropriate actions for reaching its goals, whereas undesirable outcomes can often be traced back to a lack of situation awareness prompting the wrong course of action. Modern Artificial Intelligence (AI) tools, such as Large Language Models (e.g., ChatGPT), driver assistance systems or autopilots, offer unprecedented technical capabilities of augmenting their human users’ capabilities and assisting their decision making. Yet, these have already revealed their intricacies when being deployed in complex socio-technical systems, triggering novel problems like the generation of mis- and disinformation or AI overreliance, thereby potentially rather impairing the overall system’s situation awareness and thus performance if these effects are not appropriately considered.

Therefore, the research field of cognitive situation management promotes a holistic, inherently interdisciplinary approach to addressing these challenges, incorporating the complex interactions within socio-technical-cyber systems and treating situations as first-class citizens in information processing. This involves tackling the questions of how computational systems can assess and reason upon situations and exchange this information with their human users, how to improve and measure shared situation awareness of human-machine systems, and further challenges in this realm.

Often situations involve a large number of inter-dependent dynamic entities that change their states in time and space, and engage with each other into fairly complex relations. For effectively managing situations, it is crucial to understand the situations in which these entities participate, to recognize emerging trends and potential threats, and to undertake required actions. Understanding of dynamic situations involves complex cognitive modeling of situations, building situation ontologies, and continuous sensing, perception, and comprehension of signal and human intelligence events and reports, and integrating these data into suitable presentations for supporting human and/or computational understanding of the situations. Entities participating in Situation Management need to have efficient ways of exchanging descriptions of situations.

Cognitive Situation Management thus covers analysis, modeling, and control of cyber-physical-social systems within the context of tactical and strategic goals of stakeholders, and it is based on theories and technologies of computer science, human-centered artificial intelligence, autonomous control, cognitive science and human factors research, among others. The research interests of cognitive situation management in human-centric systems as well as artificial systems built from autonomous smart software-intensive components include studies in situation awareness, situation modeling, ontologies and semantics; situation sensing, fusion, perception, comprehension, and projection; situated reasoning, situation learning and discovery, situation monitoring and control, situation management architectures and applications, situated HCI, distributing, sharing, and merging knowledge about situations; assessing truthfulness and accuracy of situation awareness, the design of systems to support human situation awareness, the development of effective approaches for integrating humans and autonomous systems.