17th Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)

1–4 June 2027 | University of Pannonia, Veszprém, Hungary

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Where Cognitive Science Meets Computer Science
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How do humans and intelligent systems understand what is happening around them — and use that understanding to predict, decide, collaborate, and act effectively and responsibly?

As AI systems increasingly move beyond specific prediction tasks toward autonomous, agentic, embodied, and human-interactive intelligence, they must perceive and integrate heterogeneous information, maintain representations of evolving environments, reason about other actors and their intentions, anticipate developments, and select appropriate actions.

At the same time, increasingly capable AI and automation raise fundamental questions about human situation awareness, appropriate reliance, shared understanding, responsibility and control, and effective human-machine collaboration. Complex operational environments involve interacting humans, machines, and hybrid systems whose performance depends not only on computational capabilities, but also on how situations are perceived, represented, interpreted, communicated, and acted upon across human and machine participants.

These are fundamentally problems of situation awareness, situation assessment, and cognitive situation management.

Now in its 17th edition, CogSIMA provides a focused international forum for studying these capabilities across human cognition, machine intelligence, and human-machine systems.

CogSIMA 2027 invites original research at the intersection of artificial intelligence and machine learning, cognitive science, human factors and ergonomics, robotics and autonomous systems, information fusion, modeling and simulation, and systems engineering.

We encourage submissions connecting established work on situation awareness and cognitive situation management with emerging areas including AI agents and agentic systems, foundation models and generative AI, multimodal reasoning, embodied AI and robotics, reinforcement learning, world models and predictive control, human–AI interaction, explainable and trustworthy AI, and multi-agent systems.

We particularly welcome work examining both the capabilities and limitations of increasingly intelligent systems: from computational situation understanding, multimodal reasoning, autonomous decision-making, and predictive models to shared situation awareness, calibrated trust, automation reliance, human oversight, explainability, responsible AI, safety, ethics, and the design of effective human-machine interaction.

CogSIMA is interested not only in what intelligent systems can do, but also in how they should interact with people, how responsibility, authority, and control should be allocated, when automation should be relied upon or questioned, and how system behavior can remain understandable, safe, and aligned with human goals in complex situations.

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WHY COGSIMA?
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A focused venue for work that crosses disciplinary boundaries

Many important questions in situation management do not fit neatly within a single research community.

How can humans and AI systems establish a shared understanding of an evolving environment?
How do people maintain situation awareness under increasing automation?
When does AI assistance improve performance, and when can it lead to overreliance, complacency, or loss of situation awareness?
How should machines reason about human goals and intentions?
How should situation awareness and situation understanding be measured and evaluated across humans, machines, and human-machine systems?

CogSIMA brings together research traditions that approach these questions from complementary perspectives. We particularly encourage contributions that connect communities – this interdisciplinary perspective is central to CogSIMA.

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Present your work – not just your paper
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CogSIMA is designed as a focused, interactive scientific meeting in which authors can discuss their work directly with researchers working across complementary disciplinary perspectives.

Accepted regular papers receive a dedicated oral presentation of approximately 15-20 minutes, providing authors with an opportunity to explain their contribution in depth and engage directly with the conference audience.

The focused single- track format is intended to foster substantive scientific exchange among students, early-career researchers, established researchers, and practitioners, and to help new researchers become part of an interdisciplinary international community.

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IS MY RESEARCH A FIT FOR COGSIMA?
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Your work may be a good fit if it addresses questions such as:

How does an AI or autonomous system represent its current situation?
How do automation and AI affect human situation awareness, workload, attention, decision-making, and performance?
How should an AI system communicate or explain its assessment of a situation to a human operator?
How can humans, robots, and AI agents establish shared situation awareness and coordinate their actions?
How can learned representations, world models, or foundation models support situation understanding, prediction, planning, or control?
How can system design support meaningful human oversight, accountability, transparency, and responsible use of AI?
How can information from humans, sensors, AI models, and other agents be fused into coherent and actionable situation representations?
How can situation-aware intelligence be deployed reliably in real- world, dynamic, uncertain, or safety-critical environments?

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TOPICS OF INTEREST
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Topics include, but are not limited to:

Situation Perception, Understanding & Representation

Human situation awareness, perception, comprehension, and projection
Situation perception, assessment, comprehension, and prediction in intelligent systems
Multisensor, multimodal, and multisource information integration and fusion
Cognitive information fusion
Mental models and cognitive representations
Knowledge representation, ontologies, and computational situation models
Context modeling and identification
Empirical methods for studying situation awareness and situated cognition

Reasoning, Prediction & Decision-Making

Human decision-making under uncertainty
Machine learning for situation understanding and management
Situation assessment in reinforcement learning
Autonomous and intelligent agents
Predictive models, world models, and model-based decision-making
Foundation models and generative AI for situated reasoning and interaction
Explainable, interpretable, trustworthy, and uncertainty-aware AI
Spatial, temporal, causal, and commonsense reasoning
Reasoning about goals, intentions, actions, and future situations
Uncertainty representation and reasoning

Human- Machine Interaction & Collaboration

Human-AI and human-robot interaction and teaming
Shared and distributed situation awareness
Human oversight and supervisory control
Adaptive automation, adjustable autonomy, and shared control
Multi- agent and mixed-initiative systems
Trust, appropriate reliance, misuse, disuse, and overreliance
Explainability, transparency, and uncertainty communication

Safety, Responsibility & Human Performance

Attention, workload, cognitive load, and adaptive performance
Automation bias, complacency, and out-of-the-loop performance
Human error and resilience
Responsible and human-centered AI
Accountability and responsibility in machine- mediated decision-making
Safety, reliability, related measures, robustness, and fail-safe interaction
Ethical and societal considerations

Systems, Evaluation & Applications

Systems, architectures, platforms, and tools for situation awareness and decision support
Benchmarks and datasets for situation-aware systems
Evaluation methodologies and metrics for human, machine, and hybrid situation awareness
Measures of human-machine team effectiveness
Real-world experiments, field studies, testbeds, and application-driven research
Safety- critical human-machine systems
Robotics and autonomous systems
Intelligent transportation and autonomous vehicles
Emergency and disaster response
Cybersecurity and cyber-physical- social systems
Cyber situation awareness and human-AI teaming in security operations
Adversarial threats to situation-aware autonomous and agentic systems
Command and control
Healthcare and medical decision support
Industrial systems and process control
Human- centric manufacturing, Operator 4.0/5.0 and industrial human-AI collaboration
Training, simulation, and decision-support environments

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SUBMISSION CATEGORIES
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CogSIMA 2027 welcomes contributions at different stages of research maturity:

Regular Papers – 6–8 pages

Regular papers should present original research advancing the state of the art through new empirical findings, computational or cognitive models, methods, algorithms, systems, experimental results, theoretical advances, or interdisciplinary contributions.

Each accepted regular paper will receive a dedicated oral presentation of approximately 15-20 minutes during the conference.

Emerging Research / Poster Papers – 3–5 pages

We explicitly welcome work in progress, emerging ideas, preliminary results, exploratory studies, novel system concepts, and promising new research directions.

Accepted papers in this category will be presented during the conference poster session and included in the conference proceedings submitted for publication in the IEEE Xplore Digital Library.

This track provides an opportunity to introduce developing research to the CogSIMA community, receive feedback, and establish connections across disciplinary boundaries.

All submissions must contain original and unpublished work that is not simultaneously under review elsewhere.

CogSIMA welcomes different forms of rigorous research, including quantitative, qualitative, and mixed-methods studies; controlled experiments and field studies; hypothesis-driven and exploratory research; computational methods and algorithms; novel system architectures and interfaces; datasets and evaluation methodologies; and interdisciplinary conceptual and methodological advances.

Depending on the nature of the contribution, submissions should clearly describe relevant methodology, experimental design, participants, measurements, environment, computational methods, system configuration, and evaluation criteria with sufficient detail to support rigorous assessment and reproducibility where applicable.

Authors must comply with the IEEE Principles of Ethical Use of Artificial Intelligence in Publishing, as specified in the current IEEE PSPB Operations Manual.

All submissions will be handled electronically through EDAS and must follow the applicable IEEE conference paper format.

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REVIEW AND PUBLICATION
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Every submission is evaluated by three independent reviewers drawn from an invited Technical Program Committee of researchers and subject- matter experts in relevant fields. Submission to CogSIMA does not entail a reviewing obligation for authors.

Submissions are evaluated based on their significance, originality, technical or empirical contribution, methodological quality, clarity, and relevance to the conference.

At least one author of every accepted paper must register at the applicable author registration rate, and accepted papers must be presented on site in Veszprém to be included in the final conference proceedings, except where an alternative presenter has been approved by the Technical Program Committee in advance.

Accepted and presented papers in both submission categories will be included in the conference proceedings submitted for publication in the IEEE Xplore Digital Library.

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VENUE
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CogSIMA 2027 will be hosted by the University of Pannonia in Veszprém, Hungary, from 1–4 June 2027.

Veszprém is one of Hungary's oldest cities and was a European Capital of Culture in 2023. Located near Lake Balaton, the largest lake in Central Europe, it combines a historic city center and active cultural life with access to one of Hungary's best-known natural and recreational regions.

Veszprém is approximately 120 km from Budapest and is accessible through Budapest's international transportation connections. It can be reached from Budapest by train in approximately 1.5 hours.