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. This ability is particularly important for robots operating around people, where behaviour is dynamic, uncertain, and strongly influenced by context. Most existing world models concentrate on physical
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experiments with people and AI systems. Some students may develop new theory or algorithms; others may use existing methods to explain behaviour in a particular setting. In either case, the aim is to
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experiments with people and AI systems. Some students may develop new theory or algorithms; others may use existing methods to explain behaviour in a particular setting. In either case, the aim is to
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behaviour. This behaviour and the drawings produced might not be the same as what humans would do. At SensiLab we have developed mobile robots that can draw. These robots serve as an experimental platform
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, which can connect structure, behaviour and function of proteins, for understanding diseases and developing drug and vaccine treatments. Modern AI techniques can provide powerful models for classifying
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-based layout is powerful, it can be difficult for users to understand the interactions and behaviour for the sometimes complex systems of constraints they have produced. While this problem has been
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-based layout is powerful, it can be difficult for users to understand the interactions and behaviour for the sometimes complex systems of constraints they have produced. While this problem has been
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’ behaviour. We will build on novel computational techniques to produce realistic enough models that can be falsified empirically [3]. Our research group studies how groups of agents can learn to cooperate
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generative AI behaviour may be constrained to within known-good parameters. Trust in Generative AI will follow into trust into the products and systems produced. The students will be expected to: (a
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generative AI behaviour may be constrained to within known-good parameters. Trust in Generative AI will follow into trust into the products and systems produced. The students will be expected to: (a