Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
In the early days a policy was a set of simple rules with a clear intuitive motivation that could be formalised to good effect. However the world is becoming much more complex. S...
Yow Tzu Lim, Pau-Chen Cheng, Pankaj Rohatgi, John ...
The successful deployment of a security policy is closely related not only to the complexity of the security requirements but also to the capabilities/functionalities of the secur...
Policy teaching considers a Markov Decision Process setting in which an interested party aims to influence an agent’s decisions by providing limited incentives. In this paper, ...
Current firewall configuration languages have no well founded semantics. Each firewall implements its own algorithm that parses specific proprietary languages. The main conseq...