Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
The behavior of a complex system often depends on parameters whose values are unknown in advance. To operate effectively, an autonomous agent must actively gather information on t...
Li Ling Ko, David Hsu, Wee Sun Lee, Sylvie C. W. O...
We optimize the full-response diagnostic fault dictionary from a given test set. The smallest set of vectors is selected without loss of diagnostic resolution of the given test se...
We describe Charm, an extensible framework designed for rapid prototyping of cryptographic systems that utilize the latest advances in cryptography, such as identity and attribute...
— We have entered an era where chip yields are decreasing with scaling. A new concept called intelligible testing has been previously proposed with the goal of reversing this tre...