This book presents different tools and techniques used for Decision Support Systems (DSS),
including decision tree and table, and their modifications, multi-criteria decision analysis …

Modeling and analyzing collective adaptive systems with heterogeneous components poses
challenges to language designers, software engineers, and computer scientists interested in …

The analysis of formal models that include quantitative aspects such as timing or
probabilistic choices is performed by quantitative verification tools. Broad and mature tool …

In life sciences, deriving insights from dynamic models can be challenging due to the large
number of state variables involved. To address this, model reduction techniques can be …

Background Stochastic models are commonly employed in the system and synthetic biology
to study the effects of stochastic fluctuations emanating from reactions involving species with …

The ability to control complex networks is of crucial importance across a wide range of
applications in natural and engineering sciences. However, issues of both theoretical and …

Simulating chemical reaction networks is often computationally demanding, in particular due
to stiffness. We propose a novel simulation scheme where long runs are not simulated as a …

The analysis of formal models that include quantitative aspects such as timing or
probabilistic choices is performed by quantitative verification tools. Broad and mature tool …

In life sciences, deriving insights from dynamical systems can be challenging due to the
large number of state variables involved. To address this, model reduction techniques can …

Self-adaptive systems provide the ability of autonomous decision-making for handling the
changes affecting the functionalities of cyber-physical systems. A self-adaptive system …