Autonomous District Shuttles for Last-Mile Delivery: Acceptance, Public Requirements, and Their Role in Urban Development
J. Kwossek, B. Eris, M. Bollien, M. Stegemann, K. Altun, M. Halbrügge, T. Jungeblut, S. Meyer, A. Pascanovic, in: HUMANIST Conference 2025, 2025.

AQ-Shuttle: Eine Studie über autonome Quartiers-Shuttle mit Mobilstation in Bielefeld
A. Kaan, B. Eris, M. Halbrügge, T. Jungeblut, R. Naumann, M. Ottemeyer, R. Öztürk, A. Pascanovic, in: 2025, pp. 2–3.

AQ-Shuttle: Autonomous Robots for Last Mile Delivery
J. Kwossek, B. Eris, M. Bollien, K. Altun, A. Pascanovic, M. Halbrügge, M. Stegemann, T. Jungeblut, in: Workshop on Autonomous Delivery and Service Robots on Pedestrian and Cycle Paths, 2025.

Statistical Learning of Daily Routines in the Smart Home for Privacy-Preserving Assisted Living
M. Halbrügge, T. Jungeblut, in: KI@HSBI 2025 - Zukunft Im Fokus, 2025, pp. 13–14.

Beyond Heatmaps: Evaluating LIME Visualizations for Human Understandability
M. Halbrügge, T. Jungeblut, in: Gesellschaft für Kognitionswissenschaft (Ed.), KogWis 2025. 16th Biannual Conference of the German Cognitive Science Society., 2025.

Digitaler Bahnhof Minden: Künstliche Intelligenz für den Bahnhof der Zukunft
H. Attaullah, M. Halbrügge, R. Naumann, T. Jungeblut, in: 2025, pp. 4–5.

Tracing Pilots’ Situation Assessment by Neuroadaptive Cognitive Modeling
O.W. Klaproth, C. Vernaleken, L.R. Krol, M. Halbrügge, T.O. Zander, N. Russwinkel, Frontiers in Neuroscience 14 (2020).

A neuroadaptive cognitive model for dealing with uncertainty in tracing pilots' cognitive state
O.W. Klaproth, M. Halbrügge, L.R. Krol, C. Vernaleken, T.O. Zander, N. Russwinkel, Topics in Cognitive Science 12 (2020).

Predicting User Performance and Errors
M. Halbrügge, Predicting User Performance and Errors, Springer International Publishing, Cham, 2018.

Towards the evaluation of cognitive models using anytime intelligence tests
M. Halbrügge, in: Technische Universität Berlin, 2016.

The sum of two models: how a composite model explains unexpected user behavior in a dual-task scenario
M. Halbrügge, N. Russwinkel, in: Technische Universität Berlin, 2016.

User Experience Measurement of a Static Website Compared to a Responsive Website Using AttrakDiff Mini
A. Fiebig, M. Halbrügge, L. Kraus, in: 2016, pp. 83–86.

Predicting user error for ambient systems by integrating model-based UI development and cognitive modeling
M. Halbrügge, M. Quade, K.-P. Engelbrecht, S. Möller, S. Albayrak, in: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, ACM, New York, NY, USA, 2016, pp. 1028–1039.

Online Calibration of Gaze Tracking on the Computer Screen using Particle Filtering
M. Halbrügge, in: SAGA - International Workshop on Solutions for Automatic Gaze Data Analysisf: Proceedings, 2015.

How Can Cognitive Modeling Benefit from Ontologies? Evidence from the HCI Domain
M. Halbrügge, M. Quade, K.-P. Engelbrecht, in: J. Bieger, B. Goertzel, A. Potapov (Eds.), Artificial General Intelligence, Springer International Publishing, Cham, 2015, pp. 261–271.

Predicting task execution times by deriving enhanced cognitive models from user interface development models
M. Quade, M. Halbrügge, K.-P. Engelbrecht, S. Albayrak, S. Möller, in: Proceedings of the 2014 ACM SIGCHI Symposium on Engineering Interactive Computing Systems, ACM, New York, NY, USA, 2014, pp. 139–148.

Keep it simple - A case study of model development in the context of the Dynamic Stocks and Flows (DSF) task
M. Halbrügge, Journal of Artificial General Intelligence 2 (2010) 38–51.

Exploration for Understanding in Cognitive Modeling
K. Gluck, C. Stanley, L. Moore, D. Reitter, M. Halbrügge, Journal of Artificial General Intelligence 2 (2010).

ACT-R Model for Predicting Performance in the DSF Task
M. Halbrügge, ACT-R Model for Predicting Performance in the DSF Task, Technische Universität Berlin, 2009.