Abstract. This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double ...
There are several situations where applications in the cloud need to self-manage their quality attributes (QA). We posit that selfadaptation can be achieved through a market-based ...
The goal of this study is to evaluate the potential for using large vocabulary continuous speech recognition as an engine for automatically classifying utterances according to the...
Steve Lowe, Anne Demedts, Larry Gillick, Mark Mand...
This paper is concerned with the problem of predicting relative performance of classification algorithms. It focusses on methods that use results on small samples and discusses th...
In this study, we explore the potential usefulness of disturbing, uncomfortable systems, demonstrating that provocative technology can have a positive effect on social relationshi...
Brooke E. Foucault, Helena M. Mentis, Phoebe Senge...