DEFINITION AND SCOPE 

Where Cognitive Science meets Computer Science 

We are proud to announce that the 2022 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA) visits Italy for the very first time, to a city filled with history: Salerno! CogSIMA 2022 will be held at the University of Salerno, Salerno, Italy, 06-10 June 2022. 

Organized by the IEEE Systems, Man and Cybernetics Society's Technical Committee on Cognitive Situation Management, the CogSIMA conference series provides the premier venue for discussing complex heterogeneous dynamical systems - of interacting humans, machines, and computer agents - whose collective behavior depends on their cognitive capabilities to comprehend, explain, predict and act upon the surrounding operational situations. 

Since 2011, the CogSIMA conferences have promoted a multidisciplinary approach to research on dynamic, cyber-physical-social systems of systems, emerging from the interaction of people, machines, computer systems and organizations situated in complex dynamic environments. Critical to these systems of systems are their cognitive and computational capabilities to (1) sense, perceive, comprehend, and predict situations, (2) reason about and recommend possible actions for situations, (3) facilitate learning, self-organization and collective intelligence, and (4) assess interdependencies between systems. Continuing in its successful, interdisciplinary tradition, CogSIMA 2022 will provide an inspiring forum for scientists and practitioners from diverse backgrounds including cognitive science, computer science, artificial intelligence, psychology, and human factors. 

Please note that Full Paper and Poster Presentation submissions are due 24 January 2022. 

TOPICS 

Topics of interest for CogSIMA include, but are not limited to: 
Situation Management – Foundations & Models 
• Advances in conceptual frameworks, architectures, models or other formalizations of situation management, decision support, and control 
• Scale in situation awareness (public vs. organizational vs. team vs. individual; distributed vs. shared awareness) 
• Situational “Big Data” analysis such as social media analytics 
• Predictive situation awareness 
• Situation modeling including anomaly and pattern detection, validation, metrics, and performance measures 
• Computer aided decision-making 
• Human-computer interfaces for situation management 
• Visualizations for situation awareness 
• Mental models and cognitive processes 
• Bio-inspired models of situation management 
• Context and knowledge representation 
• Impact of human ability (e.g., physical and/or mental impairment, demotivation) on situation management 
• Trust, including fake data 
• Self-awareness and self-* capability models and their integration into cognitive situation management 
• Artificial Intelligence (including machine learning and neural network learning) in situation management 
• Psychological aspects of situation management 
• Design, development, and adaptation of resilient systems for situation management 

Collective Situation Management and Control 
• Collective intelligence and emergent behavior in situation management 
• Cooperation and collaboration in multi-agent situation management 
• Models of collective, autonomous, and resilient situation control 
• Socially sensitive design and socially responsive design 
• Innovations in mixed initiative systems, protocols, and architectures 
• Human-centered AI and human-machine symbiosis 

Situation Management Applications 
• Pandemic and disaster situation awareness, response, and recovery 
• Cyber security situation awareness and control 
• Internet of Things (IoT), edge computing, and wearable computing 
• Cognitive robotics and human-robot interaction 
• Cyber-physical systems situation awareness, monitoring, and management 
• Autonomous vehicles and transportation systems 
• Resilient health care situation management 
• Situation management in international relations and diplomacy 
• Defense and autonomous mission control 
• Application-specific system effectiveness and performance evaluation