Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
Event based simulations are an important scientific application in many fields. With the rise of cluster computing, distributed event simulation optimization becomes an essential ...
We present an extension of the Dynamics Based Control (DBC) paradigm to environment models based on Predictive State Representations (PSRs). We show an approximate greedy version ...
Ariel Adam, Zinovi Rabinovich, Jeffrey S. Rosensch...
In this paper, we study how to, given a set of pre-routed requests in an all-optical network and a set of wavelengths available on each link, assign a subset of requests with maxim...
In this paper, we bound the difference between the total mean curvatures of two closed surfaces in R3 in terms of their total absolute curvatures and the Fr´echet distance betwee...