There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most...
In this paper we derive estimates of the sample sizes required to solve a multistage stochastic programming problem with a given accuracy by the (conditional sampling) sample aver...
Abstract. The need of true random number generators for many purposes (ranging from applications in cryptography and stochastic simulation, to search heuristics and game playing) i...
This paper describes a simulation tool for the analysis of complex jobs described in the form of task graphs. The simulation procedure relies on the PN-based topological represent...
Edges in man-made environments, grouped according to vanishing point directions, provide single-view constraints that have been exploited before as a precursor to both scene under...