In: Cancers, 2021, vol. 13, no. 19, p. 18
Artificial intelligence (AI) uses mathematical algorithms to perform tasks that require human cognitive abilities. AI-based methodologies, e.g., machine learning and deep learning, as well as the recently developed research field of radiomics have noticeable potential to transform medical diagnostics. AI-based techniques applied to medical imaging allow to detect biological abnormalities, to...
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Thèse de doctorat : Università della Svizzera italiana, 2007 ; 2007INFO001.
Ad hoc wireless multi-hop networks (AHWMNs) are communication networks that consist entirely of wireless nodes, placed together in an ad hoc manner, i.e. with minimal prior planning. All nodes have routing capabilities, and forward data packets for other nodes in multi-hop fashion. Nodes can enter or leave the network at any time, and may be mobile, so that the network topology continuously...
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Thèse de doctorat : Università della Svizzera italiana, 2008 ; 2008INFO002.
This thesis concerns the optimal behaviour of agents in unknown computable environments, also known as universal artificial intelligence. These theoretical agents are able to learn to perform optimally in many types of environments. Although they are able to optimally use prior information about the environment if it is available, in many cases they also learn to perform optimally in the absence...
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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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In: Algorithms, 2021, vol. 14, no. 9, p. 25
Recent systems applying Machine Learning (ML) to solve the Traveling Salesman Problem (TSP) exhibit issues when they try to scale up to real case scenarios with several hundred vertices. The use of Candidate Lists (CLs) has been brought up to cope with the issues. A CL is defined as a subset of all the edges linked to a given vertex such that it contains mainly edges that are believed to be...
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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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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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