The project will investigate how to develop systems that learn and reason in an artificial intelligence (AI) and autonomous systems context. While there has been a lot of progress on both machine learning and machine reasoning, their integration remains a key open challenge in artificial intelligence and autonomous systems. The distinction between learning and reasoning is related to the differences between fast and slow thinking, between data-driven and knowledge-based approaches, and between symbolic versus sub-symbolic representations. The project will build upon neuro-symbolic computation as a paradigm for integrating (neural-based) learning and symbolic reasoning. The goal of the project is to develop neural-symbolic approaches and apply them to autonomous sensor systems.