A central challenge to contemporary AI is to integrate learning and reasoning. The integration of learning and reasoning has been studied for decades already in the fields of statistical relational artificial intelligence and probabilistic programming. StarAI has focussed on unifying logic and probability, the two key frameworks for reasoning, and has extended this probabilistic logics… Continue reading Probabilistic Logics to Neuro-Symbolic Artificial Intelligence
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Robots Learning (Through) Interactions
The acquisition and self-improvement of novel motor skills is among the most important problems in robotics. I will discuss various learning techniques we developed that enable robots to have complex interactions with their environment and humans. Complexity arises from dealing with high-dimensional input data, non-linear dynamics in general and contacts in particular, multiple reference frames,… Continue reading Robots Learning (Through) Interactions
Towards Trustworthy AI – Integrating Reasoning and Learning
Europe has taken a clear stand that we want AI, but we do not want just any AI. We want AI that we can trust. This talk will present the European approach to Trustworthy AI and give an overview of some of the interesting research problems related to Trustworthy AI. Special emphasis will be placed… Continue reading Towards Trustworthy AI – Integrating Reasoning and Learning
Self-awareness for autonomous systems
Self-awareness is a broad concept borrowed from cognitive science and psychology that describes the property of a system, which has knowledge of “itself,” based on its own senses and internal models. This knowledge may take different forms, is based on perceptions of both internal and external phenomena, and is essential for being able to anticipate… Continue reading Self-awareness for autonomous systems
Intelligent Monitoring and Control of Interconnected Cyber-Physical Systems
The emergence of interconnected cyber-physical systems and sensor/actuator networks has given rise to advanced automation applications, where a large amount of sensor data is collected and processed in order to make suitable real-time decisions and to achieve the desired control objectives. However, in situations where some components behave abnormally or become faulty, this may lead… Continue reading Intelligent Monitoring and Control of Interconnected Cyber-Physical Systems
Real-World Learning
In the past decade, artificial intelligence has made remarkable progress, achieving feats like self-driving cars, defeating go-masters, and precise image categorisation through supervised deep learning with labelled data. However, a significant challenge is that deep learning models tend to be biased towards their training conditions and struggle in real-world situations that differ from their training… Continue reading Real-World Learning