The Adaptive and Cognitive Systems Lab investigates architectures and frameworks for self-learning cognitive systems that are able to adapt to an evolving environment. The lab's research revolves around integrating logic based models (ontologies), probabilistic models (Bayesian networks), and system models (multi-agent systems) for simulation; semantic event analysis, situation detection and situation prediction; representation and reasoning of spatial-temporal event patterns and cognitive vision systems. The lab has a strong applied research focus and is currently engineering systems that support data fusion, data analysis and sense making in diverse application domains, currently in health, biodiversity and earth observation.