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My research focuses on the computational modelling of intrinsic motivation, specifically examining how it can be used to shape various aspects of computational reinforcement learning. This primarily entails designing algorithms that autonomously set and pursue goals to learn diverse skills. Additionally, my work involves developing methods to evaluate open-ended learning algorithms. This evaluation is crucial for understanding the breadth and adaptability of these algorithms in learning a wide range of abilities over time.