Objectif A variety of interesting systems -- servers that fail with a certain probability; biological models, where proteins are produced with a given rate; automotive and aeronautical systems -- displays stochastic behaviour. As a fully automated method to analyse such systems, stochastic model checking is an important research area.Early techniques have suffered from several shortfalls. One of these shortfalls is that the exact failure rates of components are often unavailable. In this case, parametric models can be used, where probabilities are represented by parameters rather than values.Another shortfall is that stochastic systems are often also partially controllable. Moreover, in addition to stochastic choices, the environment of a system can be unknown or abstracted and can thus display an antagonistic behaviour. The analysis of such systems needs to account for the positive nondeterminism from the partial control over the system, the antagonistic nondeterminism that models the unknown, and the probabilistic choices. The target in this scenario is to synthesise a controller that steers the system in the best way regardless of any environment.A third shortfall is that functional properties (safety, PCTL, LTL, or w-regular goals) and non-functional goals (response time, energy usage) are analysed in isolation. When designing a system or inferring a control strategy, however, functional and non-functional properties are entangled and need to be considered in combination.While parametric analysis and the analysis of stochastic systems in isolation scale to medium size systems, the analysis of systems with mixed goals is a young and rapidly developing field. We will contribute to all three aspects, but our focus will be on studying combinations between these aspects. We will develop practically efficient techniques (as opposed to techniques with good complexity), implement them, and make them available in a tool to allow for their proliferation. Champ scientifique natural sciencesbiological sciencesbiochemistrybiomoleculesproteins Mots‑clés model checking verification Markov games and decision processes parity games control formal methods Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Thème(s) MSCA-IF-2016 - Individual Fellowships Appel à propositions H2020-MSCA-IF-2016 Voir d’autres projets de cet appel Régime de financement MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Coordinateur THE UNIVERSITY OF LIVERPOOL Contribution nette de l'UE € 195 454,80 Adresse BROWNLOW HILL 765 FOUNDATION BUILDING L69 7ZX Liverpool Royaume-Uni Voir sur la carte Région North West (England) Merseyside Liverpool Type d’activité Higher or Secondary Education Establishments Liens Contacter l’organisation Opens in new window Site web Opens in new window Participation aux programmes de R&I de l'UE Opens in new window Réseau de collaboration HORIZON Opens in new window Coût total € 195 454,80