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- Luca Bortolussi, Jane Hillston
- CONCUR
- 2012

In this paper we investigate a potential use of fluid approximation techniques in the context<lb>of stochastic model checking of CSL formulae. We focus on properties describing the behaviour<lb>of a single agent in a (large) population of agents, exploiting a limit result known also as<lb>fast simulation. In particular, we will approximate the behaviour of… (More)

- Luca Bortolussi, Alberto Policriti
- Constraints
- 2007

We present an application of stochastic Concurrent Constraint Programming (sCCP) for modeling biological systems. We provide a library of sCCP processes that can be used to describe straightforwardly biological networks. In the meanwhile, we show that sCCP proves to be a general and extensible framework, allowing to describe a wide class of dynamical… (More)

- Luca Bortolussi, Jane Hillston, Diego Latella, Mieke Massink
- Perform. Eval.
- 2013

In this paper we present an overview of the field of deterministic approximation of Markov processes, both in discrete and continuous time. We will discuss mean field approximation of discrete time Markov chains and fluid approximation of continuous time Markov chains, considering the cases in which the deterministic limit process lives in continuous time… (More)

- Federico Fogolari, Lidia Pieri, +5 authors Paolo Viglino
- BMC Structural Biology
- 2006

Reduced representations of proteins have been playing a keyrole in the study of protein folding. Many such models are available, with different representation detail. Although the usefulness of many such models for structural bioinformatics applications has been demonstrated in recent years, there are few intermediate resolution models endowed with an… (More)

- Luca Bortolussi, Dimitrios Milios, Guido Sanguinetti
- Inf. Comput.
- 2016

We consider the problem of computing the satisfaction probability of a formula for stochastic models with parametric uncertainty. We show that this satisfaction probability is a smooth function of the model parameters. This enables us to devise a novel Bayesian statistical algorithm which performs model checking simultaneously for all values of the model… (More)

- Luca Bortolussi, Roberta Lanciani
- QEST
- 2013

- Luca Bortolussi, Alberto Policriti
- Theor. Comput. Sci.
- 2010

We explore the possibility of designing a constraint-based algorithm for constructing subsets of DNA words satisfying given constraints (the so-called DNA word design problem). In this direction, we use symbolic representation of sets of strings, and define a propagation algorithm on these representations. Some preliminary results are presented, together… (More)

We present Signal Spatio-Temporal Logic (SSTL), a modal logic that can be used to specify spatio-temporal properties in linear time and for a discrete space. The logic is equipped with a Boolean and a quantitative semantics, and with accompanying monitoring algorithms. As such, it is suitable for real-time verification of both white box and black box… (More)

- Luca Bortolussi, Richard A. Hayden
- Perform. Eval.
- 2013

We consider a generic mean-field scenario, in which a sequence of population models, described by discretetime Markov chains (DTMCs), converges to a deterministic limit in discrete time. Under the assumption that the limit has a globally attracting equilibrium, the steady states of the sequence of DTMC models converge to the point-mass distribution… (More)