— In this paper, we lay the groundwork for extending our previously developed ASyMTRe architecture to enable constructivist learning for multi-robot team tasks. The ASyMTRe archi...
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
In recent years, corpus based approaches to machine translation have become predominant, with Statistical Machine Translation (SMT) being the most actively progressing area. Succe...
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
The key to high performance in Simultaneous Multithreaded (SMT) processors lies in optimizing the distribution of shared resources to active threads. Existing resource distributio...