Predicting accurately the spatiotemporal evolution of a diffusive environmental hazard is of paramount importance for its effective containment. We approximate the front line of a...
Many self-organizing and self-adaptive systems use the biologically inspired “gradient” primitive, in which each device in a network estimates its distance to the closest devi...
Jonathan Bachrach, Jacob Beal, Joshua Horowitz, Da...
Model predictive control (MPC) is of interest because it is one of the few control design methods which preserves standard design variables and yet handles constraints. MPC is nor...
We give a description of a Petri net-based framework for modelling and analysing biochemical pathways, which unifies the qualitative, stochastic and continuous paradigms. Each per...
It is well-known that, in unidentifiable models, the Bayes estimation provides much better generalization performance than the maximum likelihood (ML) estimation. However, its ac...