— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Modern digital libraries require user-friendly and yet responsive access to the rapidly growing, heterogeneous, and distributed collection of information sources. However, the inc...
Network intrusion detection systems (NIDSs) critically rely on processing a great deal of state. Often much of this state resides solely in the volatile processor memory accessibl...
ion. First described in RFC 707,1 with implementation approaches and details later provided by Andrew Birrell and Bruce Nelson,2 RPC has influenced distributed systems research and...