2019 Proceeding- Program Chairs:
- Sriram Sankaranarayanan,
- Sadegh Soudjani
SNR19 focuses on the combination of symbolic and numeric methods for reasoning about Cyber-Physical Systems and the Internet of Things to facilitate model identification, specification, verification, and control synthesis problems for these systems. The synergy between symbolic and numerical approaches is fruitful for two main reasons:
•Symbolic methods that operate on exact and discrete representations of systems, the set of reachable states, the distribution of model parameters or the possible gains for controller parameters.
•Numeric methods that operate on various forms of numerical approximations and continuous transformations of the systems, as developed in the area of continuous dynamical systems and control theory.
Proceeding Downloads
Symbolic-numeric methods in reasoning about the design of future air traffic management
In our busy skies and airports, commercial aviation critically depends on air traffic management (ATM). ATM forms a complex Cyber Physical Human System (CPHS) that involves dynamic interactions under uncertainties (e.g. weather) between distributed ...
Compositional finite abstractions for large-scale stochastic switched systems
In this paper, we provide for the first time a compositional methodology for the construction of finite MDPs for networks of stochastic switched systems. The proposed technique leverages sufficient small-gain type conditions to establish the ...
Correct-by-construction policies for POMDPs
- Nils Jansen,
- Sebastian Junges,
- Joost-Pieter Katoen,
- Tim Quatmann,
- Bernd Becker,
- Ralf Wimmer,
- Leonore Winterer
Summary. In this extended abstract, we discuss how to compute policies with finite memory---so-called finite-state controllers (FSCs)---for partially observable Markov decision processes (POMDPs) that are provably correct with respect to given ...
Sampling-free enforcement of non-gaussian chance constraints via fourier transforms
Verification of stochastic dynamical systems can often be formulated as chance-constrained optimization problems - maximize probability of satisfaction of safety/reachability objectives subject to dynamics and control bounds. For linear systems ...
Achievements in correct-by-design control for stochastic systems
Discrete-time stochastic systems are an essential modeling tool for many engineering systems. The direct synthesis of controllers for guaranteeing temporal properties encoded as finite automata has gain significant attention. Still, for many physical ...
Limit reachability for model-free reinforcement learning of ω-regular objectives
We have recently solved the model-free reinforcement learning of ω-regular objectives for Markov decision processes. We outline our constructive reduction from the almost-sure satisfaction of ω-regular objectives to an almost-sure reachability problem, ...
Preview of predictive monitoring for signal temporal logic with probabilistic guarantees
Monitoring is an effective approach for identifying safety violations for complex cyber-physical systems. In this paper, we consider safety specifications expressed in Signal Temporal Logic (STL). STL is a logic for specifying timed properties of real-...
Falsification of cyber-physical systems through multi-fidelity stochastic optimization
This talk will review some recent results on requirements driven search-based testing for Cyber-Physical Systems (CPS). Namely, we will present an extension to a Bayesian optimizer that makes use of models of different complexity (and accuracy) that ...
Neural state classification for hybrid systems
Model checking of hybrid systems is usually expressed in terms of the following reachability problem for hybrid automata (HA) [6]: given an HA M, a set of initial states I, and a set of unsafe states U, determine whether there exists a trajectory of M ...
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