Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020INFO019.
Deep neural networks learn representations of data to facilitate problem-solving in their respective domains. However, they struggle to acquire a structured representation based on more symbolic entities, which are commonly understood as core abstractions central to human capacity for generalization. This dissertation studies this issue for visual reasoning tasks. Inspired by how humans solve...
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Thèse de doctorat : Università della Svizzera italiana, 2014 ; 2014INFO020.
Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the...
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Thèse de doctorat : Università della Svizzera italiana, 2012 ; 2012INFO001.
Creating autonomous agents that learn to act from sequential interactions has long been perceived as one of the ultimate goals of Artificial Intelligence (AI). Reinforcement Learning (RL), a subfield of Machine Learning (ML), addresses important aspects of this objective. This dissertation investigates a particular problem encountered in RL called representation generation. Two related...
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