@inproceedings{79, abstract = {Markov Decision Processes (MDPs) are a popular class of models suitable for solving control decision problems in probabilistic reactive systems. We consider parametric MDPs (pMDPs) that include parameters in some of the transition probabilities to account for stochastic uncertainties of the environment such as noise or input disturbances. We study pMDPs with reachability objectives where the parameter values are unknown and impossible to measure directly during execution, but there is a probability distribution known over the parameter values. We study for the first time computing parameter-independent strategies that are expectation optimal, i.e., optimize the expected reachability probability under the probability distribution over the parameters. We present an encoding of our problem to partially observable MDPs (POMDPs), i.e., a reduction of our problem to computing optimal strategies in POMDPs. We evaluate our method experimentally on several benchmarks: a motivating (repeated) learner model; a series of benchmarks of varying configurations of a robot moving on a grid; and a consensus protocol.}, author = {Arming, Sebastian and Bartocci, Ezio and Chatterjee, Krishnendu and Katoen, Joost P and Sokolova, Ana}, location = {Beijing, China}, pages = {53--70}, publisher = {Springer}, title = {{Parameter-independent strategies for pMDPs via POMDPs}}, doi = {10.1007/978-3-319-99154-2_4}, volume = {11024}, year = {2018}, } @inproceedings{142, abstract = {We address the problem of analyzing the reachable set of a polynomial nonlinear continuous system by over-approximating the flowpipe of its dynamics. The common approach to tackle this problem is to perform a numerical integration over a given time horizon based on Taylor expansion and interval arithmetic. However, this method results to be very conservative when there is a large difference in speed between trajectories as time progresses. In this paper, we propose to use combinations of barrier functions, which we call piecewise barrier tube (PBT), to over-approximate flowpipe. The basic idea of PBT is that for each segment of a flowpipe, a coarse box which is big enough to contain the segment is constructed using sampled simulation and then in the box we compute by linear programming a set of barrier functions (called barrier tube or BT for short) which work together to form a tube surrounding the flowpipe. The benefit of using PBT is that (1) BT is independent of time and hence can avoid being stretched and deformed by time; and (2) a small number of BTs can form a tight over-approximation for the flowpipe, which means that the computation required to decide whether the BTs intersect the unsafe set can be reduced significantly. We implemented a prototype called PBTS in C++. Experiments on some benchmark systems show that our approach is effective.}, author = {Kong, Hui and Bartocci, Ezio and Henzinger, Thomas A}, location = {Oxford, United Kingdom}, pages = {449 -- 467}, publisher = {Springer}, title = {{Reachable set over-approximation for nonlinear systems using piecewise barrier tubes}}, doi = {10.1007/978-3-319-96145-3_24}, volume = {10981}, year = {2018}, } @article{434, abstract = {In this paper, we present a formal model-driven design approach to establish a safety-assured implementation of multifunction vehicle bus controller (MVBC), which controls the data transmission among the devices of the vehicle. First, the generic models and safety requirements described in International Electrotechnical Commission Standard 61375 are formalized as time automata and timed computation tree logic formulas, respectively. With model checking tool Uppaal, we verify whether or not the constructed timed automata satisfy the formulas and several logic inconsistencies in the original standard are detected and corrected. Then, we apply the code generation tool Times to generate C code from the verified model, which is later synthesized into a real MVBC chip, with some handwriting glue code. Furthermore, the runtime verification tool RMOR is applied on the integrated code, to verify some safety requirements that cannot be formalized on the timed automata. For evaluation, we compare the proposed approach with existing MVBC design methods, such as BeagleBone, Galsblock, and Simulink. Experiments show that more ambiguousness or bugs in the standard are detected during Uppaal verification, and the generated code of Times outperforms the C code generated by others in terms of the synthesized binary code size. The errors in the standard have been confirmed and the resulting MVBC has been deployed in the real train communication network.}, author = {Jiang, Yu and Liu, Han and Song, Huobing and Kong, Hui and Wang, Rui and Guan, Yong and Sha, Lui}, journal = {IEEE Transactions on Intelligent Transportation Systems}, number = {10}, pages = {3320 -- 3333}, publisher = {IEEE}, title = {{Safety-assured model-driven design of the multifunction vehicle bus controller}}, doi = {10.1109/TITS.2017.2778077}, volume = {19}, year = {2018}, } @inproceedings{140, abstract = {Reachability analysis is difficult for hybrid automata with affine differential equations, because the reach set needs to be approximated. Promising abstraction techniques usually employ interval methods or template polyhedra. Interval methods account for dense time and guarantee soundness, and there are interval-based tools that overapproximate affine flowpipes. But interval methods impose bounded and rigid shapes, which make refinement expensive and fixpoint detection difficult. Template polyhedra, on the other hand, can be adapted flexibly and can be unbounded, but sound template refinement for unbounded reachability analysis has been implemented only for systems with piecewise constant dynamics. We capitalize on the advantages of both techniques, combining interval arithmetic and template polyhedra, using the former to abstract time and the latter to abstract space. During a CEGAR loop, whenever a spurious error trajectory is found, we compute additional space constraints and split time intervals, and use these space-time interpolants to eliminate the counterexample. Space-time interpolation offers a lazy, flexible framework for increasing precision while guaranteeing soundness, both for error avoidance and fixpoint detection. To the best of out knowledge, this is the first abstraction refinement scheme for the reachability analysis over unbounded and dense time of affine hybrid systems, which is both sound and automatic. We demonstrate the effectiveness of our algorithm with several benchmark examples, which cannot be handled by other tools.}, author = {Frehse, Goran and Giacobbe, Mirco and Henzinger, Thomas A}, issn = {03029743}, location = {Oxford, United Kingdom}, pages = {468 -- 486}, publisher = {Springer}, title = {{Space-time interpolants}}, doi = {10.1007/978-3-319-96145-3_25}, volume = {10981}, year = {2018}, } @inproceedings{297, abstract = {Graph games played by two players over finite-state graphs are central in many problems in computer science. In particular, graph games with ω -regular winning conditions, specified as parity objectives, which can express properties such as safety, liveness, fairness, are the basic framework for verification and synthesis of reactive systems. The decisions for a player at various states of the graph game are represented as strategies. While the algorithmic problem for solving graph games with parity objectives has been widely studied, the most prominent data-structure for strategy representation in graph games has been binary decision diagrams (BDDs). However, due to the bit-level representation, BDDs do not retain the inherent flavor of the decisions of strategies, and are notoriously hard to minimize to obtain succinct representation. In this work we propose decision trees for strategy representation in graph games. Decision trees retain the flavor of decisions of strategies and allow entropy-based minimization to obtain succinct trees. However, decision trees work in settings (e.g., probabilistic models) where errors are allowed, and overfitting of data is typically avoided. In contrast, for strategies in graph games no error is allowed, and the decision tree must represent the entire strategy. We develop new techniques to extend decision trees to overcome the above obstacles, while retaining the entropy-based techniques to obtain succinct trees. We have implemented our techniques to extend the existing decision tree solvers. We present experimental results for problems in reactive synthesis to show that decision trees provide a much more efficient data-structure for strategy representation as compared to BDDs.}, author = {Brázdil, Tomáš and Chatterjee, Krishnendu and Kretinsky, Jan and Toman, Viktor}, location = {Thessaloniki, Greece}, pages = {385 -- 407}, publisher = {Springer}, title = {{Strategy representation by decision trees in reactive synthesis}}, doi = {10.1007/978-3-319-89960-2_21}, volume = {10805}, year = {2018}, } @article{608, abstract = {Synthesis is the automated construction of a system from its specification. In real life, hardware and software systems are rarely constructed from scratch. Rather, a system is typically constructed from a library of components. Lustig and Vardi formalized this intuition and studied LTL synthesis from component libraries. In real life, designers seek optimal systems. In this paper we add optimality considerations to the setting. We distinguish between quality considerations (for example, size - the smaller a system is, the better it is), and pricing (for example, the payment to the company who manufactured the component). We study the problem of designing systems with minimal quality-cost and price. A key point is that while the quality cost is individual - the choices of a designer are independent of choices made by other designers that use the same library, pricing gives rise to a resource-allocation game - designers that use the same component share its price, with the share being proportional to the number of uses (a component can be used several times in a design). We study both closed and open settings, and in both we solve the problem of finding an optimal design. In a setting with multiple designers, we also study the game-theoretic problems of the induced resource-allocation game.}, author = {Avni, Guy and Kupferman, Orna}, journal = {Theoretical Computer Science}, pages = {50 -- 72}, publisher = {Elsevier}, title = {{Synthesis from component libraries with costs}}, doi = {10.1016/j.tcs.2017.11.001}, volume = {712}, year = {2018}, } @inproceedings{156, abstract = {Imprecision in timing can sometimes be beneficial: Metric interval temporal logic (MITL), disabling the expression of punctuality constraints, was shown to translate to timed automata, yielding an elementary decision procedure. We show how this principle extends to other forms of dense-time specification using regular expressions. By providing a clean, automaton-based formal framework for non-punctual languages, we are able to recover and extend several results in timed systems. Metric interval regular expressions (MIRE) are introduced, providing regular expressions with non-singular duration constraints. We obtain that MIRE are expressively complete relative to a class of one-clock timed automata, which can be determinized using additional clocks. Metric interval dynamic logic (MIDL) is then defined using MIRE as temporal modalities. We show that MIDL generalizes known extensions of MITL, while translating to timed automata at comparable cost.}, author = {Ferrere, Thomas}, location = {Oxford, UK}, pages = {147 -- 164}, publisher = {Springer}, title = {{The compound interest in relaxing punctuality}}, doi = {10.1007/978-3-319-95582-7_9}, volume = {10951}, year = {2018}, } @inproceedings{5959, abstract = {Formalizing properties of systems with continuous dynamics is a challenging task. In this paper, we propose a formal framework for specifying and monitoring rich temporal properties of real-valued signals. We introduce signal first-order logic (SFO) as a specification language that combines first-order logic with linear-real arithmetic and unary function symbols interpreted as piecewise-linear signals. We first show that while the satisfiability problem for SFO is undecidable, its membership and monitoring problems are decidable. We develop an offline monitoring procedure for SFO that has polynomial complexity in the size of the input trace and the specification, for a fixed number of quantifiers and function symbols. We show that the algorithm has computation time linear in the size of the input trace for the important fragment of bounded-response specifications interpreted over input traces with finite variability. We can use our results to extend signal temporal logic with first-order quantifiers over time and value parameters, while preserving its efficient monitoring. We finally demonstrate the practical appeal of our logic through a case study in the micro-electronics domain.}, author = {Bakhirkin, Alexey and Ferrere, Thomas and Henzinger, Thomas A and Nickovicl, Deian}, booktitle = {2018 International Conference on Embedded Software}, isbn = {9781538655603}, location = {Turin, Italy}, pages = {1--10}, publisher = {IEEE}, title = {{Keynote: The first-order logic of signals}}, doi = {10.1109/emsoft.2018.8537203}, year = {2018}, } @inproceedings{24, abstract = {Partially-observable Markov decision processes (POMDPs) with discounted-sum payoff are a standard framework to model a wide range of problems related to decision making under uncertainty. Traditionally, the goal has been to obtain policies that optimize the expectation of the discounted-sum payoff. A key drawback of the expectation measure is that even low probability events with extreme payoff can significantly affect the expectation, and thus the obtained policies are not necessarily risk-averse. An alternate approach is to optimize the probability that the payoff is above a certain threshold, which allows obtaining risk-averse policies, but ignores optimization of the expectation. We consider the expectation optimization with probabilistic guarantee (EOPG) problem, where the goal is to optimize the expectation ensuring that the payoff is above a given threshold with at least a specified probability. We present several results on the EOPG problem, including the first algorithm to solve it.}, author = {Chatterjee, Krishnendu and Elgyütt, Adrian and Novotny, Petr and Rouillé, Owen}, location = {Stockholm, Sweden}, pages = {4692 -- 4699}, publisher = {IJCAI}, title = {{Expectation optimization with probabilistic guarantees in POMDPs with discounted-sum objectives}}, doi = {10.24963/ijcai.2018/652}, volume = {2018}, year = {2018}, } @article{6006, abstract = {Network games (NGs) are played on directed graphs and are extensively used in network design and analysis. Search problems for NGs include finding special strategy profiles such as a Nash equilibrium and a globally-optimal solution. The networks modeled by NGs may be huge. In formal verification, abstraction has proven to be an extremely effective technique for reasoning about systems with big and even infinite state spaces. We describe an abstraction-refinement methodology for reasoning about NGs. Our methodology is based on an abstraction function that maps the state space of an NG to a much smaller state space. We search for a global optimum and a Nash equilibrium by reasoning on an under- and an over-approximation defined on top of this smaller state space. When the approximations are too coarse to find such profiles, we refine the abstraction function. We extend the abstraction-refinement methodology to labeled networks, where the objectives of the players are regular languages. Our experimental results demonstrate the effectiveness of the methodology. }, author = {Avni, Guy and Guha, Shibashis and Kupferman, Orna}, issn = {2073-4336}, journal = {Games}, number = {3}, publisher = {MDPI AG}, title = {{An abstraction-refinement methodology for reasoning about network games}}, doi = {10.3390/g9030039}, volume = {9}, year = {2018}, }