Optimistic No-regret Algorithms for Discrete Caching

We take a systematic look at the problem of storing whole files in a cache with limited capacity in the context of optimistic learning, where the caching policy has access to a prediction oracle. The successive file requests are assumed to be generated by an adversary, and no assumption is made on the accuracy of the oracle. We provide a...

Generalized Models of Sequential Decision-Making under Uncertainty

Sequential decision-making under uncertainty is an important branch of artificial intelligence research with a plethora of real-life applications. In this thesis, we generalize two fundamental properties of the decision-making process. First, we show that the theory on planning methods for finite spaces can be extended to infinite but countable...