David Leslie

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—We present a Bayesian reinforcement learning model with a working memory module which can solve some non-Markovian decision processes. The model is tested, and compared against SARSA(λ), on a standard working-memory task from the psychology literature. Our method uses the Kalman temporal difference framework , and its extension to stochastic state(More)
We examine a FlipIt game in which there are multiple resources which a monolithic attacker is trying to compromise. This extension to FlipIt was considered in a paper in GameSec 2014, and was there called FlipThem. Our analysis of such a situation is focused on the situation where the attacker's goal is to compromise a threshold of the resources. We use our(More)
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