The growth in the scale of systems and networks has created many challenges for their management, especially for event processing. Our premise is that scaling event processing requ...
Wei Xu, Joseph L. Hellerstein, Bill Kramer, David ...
Sensor network applications face continuously changing environments, which impose varying processing loads on the sensor node. This paper presents an online control method which a...
Abstract. In [8] Yamauchi and Beer explored the abilities of continuous time recurrent neural networks (CTRNNs) to display reinforcementlearning like abilities. The investigated ta...
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
— Developing and managing firewall Access Control Lists (ACLs) are hard, time-consuming, and error-prone tasks for a variety of reasons. Complexity of networks is constantly incr...