— Reinforcement Learning (RL) provides a promising new approach to systems performance management that differs radically from standard queuing-theoretic approaches making use of ...
Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mo...
Traditional problem determination techniques rely on static dependency models that are difficult to generate accurately in today’s large, distributed, and dynamic application e...
Mike Y. Chen, Emre Kiciman, Eugene Fratkin, Armand...
Dynamic information flow policies, such as declassification, are essential for practically useful information flow control systems. However, most systems proposed to date that ...
Electronic negotiation experiments provide a rich source of information about relationships between the negotiators, their individual actions, and the negotiation dynami...
In this paper, we address the problem of representing human actions using visual cues for the purpose of learning and recognition. Traditional approaches model actions as space-ti...