We develop a framework for automated optimization of stochastic simulation models using Response Surface Methodology. The framework is especially intended for simulation models wh...
H. Gonda Neddermeijer, Gerrit J. van Oortmarssen, ...
— Modeling robot motion planning with uncertainty in a Bayesian framework leads to a computationally intractable stochastic control problem. We seek hypotheses that can justify a...
Andrea Censi, Daniele Calisi, Alessandro De Luca, ...
We describe a generic framework for integrating various stochastic models of discourse coherence in a manner that takes advantage of their individual strengths. An integral part o...
This paper demonstrates how three stochastic process algebras can be mapped on to a generally-distributed stochastic transition system. We demonstrate an aggregation technique on ...
—The main contribution of this paper arises from the development of a new framework, which has its inspiration in the mechanics of human navigation, for solving the problem of Si...