Searcharxiv⌕ Search

arXiv subjects

Elizabeth Polgreen

Publications and source records attributed to Elizabeth Polgreen.

21 records · Page 2Linked to original sources

Verifying Reachability Properties in Markov Chains via Incremental Induction

There is a scalability gap between probabilistic and non-probabilistic verification. Probabilistic model checking tools are based either on explicit engines or on (Multi-Terminal) Binary Decision Diagrams. These structures are complemented in areas of non-probabilistic verification by more scalable techniques, such as IC3. We present a symbolic probabilistic model checking algorithm based on IC3-like incremental construction of inductive clauses to partition the state space, interleaved with incremental construction of a system of linear inequalities. This paper compares our implementation to standard quantitative verification alternatives: our experiments show that our algorithm is a step to more scalable symbolic verification of rare events in finite-state Markov chains.

cs.LO↗

Automated Experiment Design for Data-Efficient Verification of Parametric Markov Decision Processes

We present a new method for statistical verification of quantitative properties over a partially unknown system with actions, utilising a parameterised model (in this work, a parametric Markov decision process) and data collected from experiments performed on the underlying system. We obtain the confidence that the underlying system satisfies a given property, and show that the method uses data efficiently and thus is robust to the amount of data available. These characteristics are achieved by firstly exploiting parameter synthesis to establish a feasible set of parameters for which the underlying system will satisfy the property; secondly, by actively synthesising experiments to increase amount of information in the collected data that is relevant to the property; and finally propagating this information over the model parameters, obtaining a confidence that reflects our belief whether or not the system parameters lie in the feasible set, thereby solving the verification problem.

cs.LG↗

Automated Formal Synthesis of Digital Controllers for State-Space Physical Plants

We present a sound and automated approach to synthesize safe digital feedback controllers for physical plants represented as linear, time invariant models. Models are given as dynamical equations with inputs, evolving over a continuous state space and accounting for errors due to the digitalization of signals by the controller. Our approach has two stages, leveraging counterexample guided inductive synthesis (CEGIS) and reachability analysis. CEGIS synthesizes a static feedback controller that stabilizes the system under restrictions given by the safety of the reach space. Safety is verified either via BMC or abstract acceleration; if the verification step fails, we refine the controller by generalizing the counterexample. We synthesize stable and safe controllers for intricate physical plant models from the digital control literature.

eess.SY↗