@inproceedings{1601, abstract = {We propose a flexible exchange format for ω-automata, as typically used in formal verification, and implement support for it in a range of established tools. Our aim is to simplify the interaction of tools, helping the research community to build upon other people’s work. A key feature of the format is the use of very generic acceptance conditions, specified by Boolean combinations of acceptance primitives, rather than being limited to common cases such as Büchi, Streett, or Rabin. Such flexibility in the choice of acceptance conditions can be exploited in applications, for example in probabilistic model checking, and furthermore encourages the development of acceptance-agnostic tools for automata manipulations. The format allows acceptance conditions that are either state-based or transition-based, and also supports alternating automata.}, author = {Babiak, Tomáš and Blahoudek, František and Duret Lutz, Alexandre and Klein, Joachim and Kretinsky, Jan and Mueller, Daniel and Parker, David and Strejček, Jan}, location = {San Francisco, CA, United States}, pages = {479 -- 486}, publisher = {Springer}, title = {{The Hanoi omega-automata format}}, doi = {10.1007/978-3-319-21690-4_31}, volume = {9206}, year = {2015}, } @article{1602, abstract = {Interprocedural analysis is at the heart of numerous applications in programming languages, such as alias analysis, constant propagation, etc. Recursive state machines (RSMs) are standard models for interprocedural analysis. We consider a general framework with RSMs where the transitions are labeled from a semiring, and path properties are algebraic with semiring operations. RSMs with algebraic path properties can model interprocedural dataflow analysis problems, the shortest path problem, the most probable path problem, etc. The traditional algorithms for interprocedural analysis focus on path properties where the starting point is fixed as the entry point of a specific method. In this work, we consider possible multiple queries as required in many applications such as in alias analysis. The study of multiple queries allows us to bring in a very important algorithmic distinction between the resource usage of the one-time preprocessing vs for each individual query. The second aspect that we consider is that the control flow graphs for most programs have constant treewidth. Our main contributions are simple and implementable algorithms that supportmultiple queries for algebraic path properties for RSMs that have constant treewidth. Our theoretical results show that our algorithms have small additional one-time preprocessing, but can answer subsequent queries significantly faster as compared to the current best-known solutions for several important problems, such as interprocedural reachability and shortest path. We provide a prototype implementation for interprocedural reachability and intraprocedural shortest path that gives a significant speed-up on several benchmarks.}, author = {Chatterjee, Krishnendu and Ibsen-Jensen, Rasmus and Pavlogiannis, Andreas and Goyal, Prateesh}, journal = {ACM SIGPLAN Notices}, location = {Mumbai, India}, number = {1}, pages = {97 -- 109}, publisher = {ACM}, title = {{Faster algorithms for algebraic path properties in recursive state machines with constant treewidth}}, doi = {10.1145/2676726.2676979}, volume = {50}, year = {2015}, } @inproceedings{1603, abstract = {For deterministic systems, a counterexample to a property can simply be an error trace, whereas counterexamples in probabilistic systems are necessarily more complex. For instance, a set of erroneous traces with a sufficient cumulative probability mass can be used. Since these are too large objects to understand and manipulate, compact representations such as subchains have been considered. In the case of probabilistic systems with non-determinism, the situation is even more complex. While a subchain for a given strategy (or scheduler, resolving non-determinism) is a straightforward choice, we take a different approach. Instead, we focus on the strategy itself, and extract the most important decisions it makes, and present its succinct representation. The key tools we employ to achieve this are (1) introducing a concept of importance of a state w.r.t. the strategy, and (2) learning using decision trees. There are three main consequent advantages of our approach. Firstly, it exploits the quantitative information on states, stressing the more important decisions. Secondly, it leads to a greater variability and degree of freedom in representing the strategies. Thirdly, the representation uses a self-explanatory data structure. In summary, our approach produces more succinct and more explainable strategies, as opposed to e.g. binary decision diagrams. Finally, our experimental results show that we can extract several rules describing the strategy even for very large systems that do not fit in memory, and based on the rules explain the erroneous behaviour.}, author = {Brázdil, Tomáš and Chatterjee, Krishnendu and Chmelik, Martin and Fellner, Andreas and Kretinsky, Jan}, location = {San Francisco, CA, United States}, pages = {158 -- 177}, publisher = {Springer}, title = {{Counterexample explanation by learning small strategies in Markov decision processes}}, doi = {10.1007/978-3-319-21690-4_10}, volume = {9206}, year = {2015}, } @article{1604, abstract = {We consider the quantitative analysis problem for interprocedural control-flow graphs (ICFGs). The input consists of an ICFG, a positive weight function that assigns every transition a positive integer-valued number, and a labelling of the transitions (events) as good, bad, and neutral events. The weight function assigns to each transition a numerical value that represents ameasure of how good or bad an event is. The quantitative analysis problem asks whether there is a run of the ICFG where the ratio of the sum of the numerical weights of good events versus the sum of weights of bad events in the long-run is at least a given threshold (or equivalently, to compute the maximal ratio among all valid paths in the ICFG). The quantitative analysis problem for ICFGs can be solved in polynomial time, and we present an efficient and practical algorithm for the problem. We show that several problems relevant for static program analysis, such as estimating the worst-case execution time of a program or the average energy consumption of a mobile application, can be modeled in our framework. We have implemented our algorithm as a tool in the Java Soot framework. We demonstrate the effectiveness of our approach with two case studies. First, we show that our framework provides a sound approach (no false positives) for the analysis of inefficiently-used containers. Second, we show that our approach can also be used for static profiling of programs which reasons about methods that are frequently invoked. Our experimental results show that our tool scales to relatively large benchmarks, and discovers relevant and useful information that can be used to optimize performance of the programs.}, author = {Chatterjee, Krishnendu and Pavlogiannis, Andreas and Velner, Yaron}, isbn = {978-1-4503-3300-9}, journal = {Proceedings of the 42nd Annual ACM SIGPLAN-SIGACT }, location = {Mumbai, India}, number = {1}, pages = {539 -- 551}, publisher = {ACM}, title = {{Quantitative interprocedural analysis}}, doi = {10.1145/2676726.2676968}, volume = {50}, year = {2015}, } @inproceedings{1607, abstract = {We consider the core algorithmic problems related to verification of systems with respect to three classical quantitative properties, namely, the mean-payoff property, the ratio property, and the minimum initial credit for energy property. The algorithmic problem given a graph and a quantitative property asks to compute the optimal value (the infimum value over all traces) from every node of the graph. We consider graphs with constant treewidth, and it is well-known that the control-flow graphs of most programs have constant treewidth. Let n denote the number of nodes of a graph, m the number of edges (for constant treewidth graphs m=O(n)) and W the largest absolute value of the weights. Our main theoretical results are as follows. First, for constant treewidth graphs we present an algorithm that approximates the mean-payoff value within a multiplicative factor of ϵ in time O(n⋅log(n/ϵ)) and linear space, as compared to the classical algorithms that require quadratic time. Second, for the ratio property we present an algorithm that for constant treewidth graphs works in time O(n⋅log(|a⋅b|))=O(n⋅log(n⋅W)), when the output is ab, as compared to the previously best known algorithm with running time O(n2⋅log(n⋅W)). Third, for the minimum initial credit problem we show that (i) for general graphs the problem can be solved in O(n2⋅m) time and the associated decision problem can be solved in O(n⋅m) time, improving the previous known O(n3⋅m⋅log(n⋅W)) and O(n2⋅m) bounds, respectively; and (ii) for constant treewidth graphs we present an algorithm that requires O(n⋅logn) time, improving the previous known O(n4⋅log(n⋅W)) bound. We have implemented some of our algorithms and show that they present a significant speedup on standard benchmarks.}, author = {Chatterjee, Krishnendu and Ibsen-Jensen, Rasmus and Pavlogiannis, Andreas}, location = {San Francisco, CA, USA}, pages = {140 -- 157}, publisher = {Springer}, title = {{Faster algorithms for quantitative verification in constant treewidth graphs}}, doi = {10.1007/978-3-319-21690-4_9}, volume = {9206}, year = {2015}, } @inproceedings{1609, abstract = {The synthesis problem asks for the automatic construction of a system from its specification. In the traditional setting, the system is “constructed from scratch” rather than composed from reusable components. However, this is rare in practice, and almost every non-trivial software system relies heavily on the use of libraries of reusable components. Recently, Lustig and Vardi introduced dataflow and controlflow synthesis from libraries of reusable components. They proved that dataflow synthesis is undecidable, while controlflow synthesis is decidable. The problem of controlflow synthesis from libraries of probabilistic components was considered by Nain, Lustig and Vardi, and was shown to be decidable for qualitative analysis (that asks that the specification be satisfied with probability 1). Our main contribution for controlflow synthesis from probabilistic components is to establish better complexity bounds for the qualitative analysis problem, and to show that the more general quantitative problem is undecidable. For the qualitative analysis, we show that the problem (i) is EXPTIME-complete when the specification is given as a deterministic parity word automaton, improving the previously known 2EXPTIME upper bound; and (ii) belongs to UP ∩ coUP and is parity-games hard, when the specification is given directly as a parity condition on the components, improving the previously known EXPTIME upper bound.}, author = {Chatterjee, Krishnendu and Doyen, Laurent and Vardi, Moshe}, booktitle = {42nd International Colloquium}, isbn = {978-3-662-47665-9}, location = {Kyoto, Japan}, pages = {108 -- 120}, publisher = {Springer Nature}, title = {{The complexity of synthesis from probabilistic components}}, doi = {10.1007/978-3-662-47666-6_9}, volume = {9135}, year = {2015}, } @inproceedings{1610, abstract = {The edit distance between two words w1, w2 is the minimal number of word operations (letter insertions, deletions, and substitutions) necessary to transform w1 to w2. The edit distance generalizes to languages L1,L2, where the edit distance is the minimal number k such that for every word from L1 there exists a word in L2 with edit distance at most k. We study the edit distance computation problem between pushdown automata and their subclasses. The problem of computing edit distance to pushdown automata is undecidable, and in practice, the interesting question is to compute the edit distance from a pushdown automaton (the implementation, a standard model for programs with recursion) to a regular language (the specification). In this work, we present a complete picture of decidability and complexity for deciding whether, for a given threshold k, the edit distance from a pushdown automaton to a finite automaton is at most k.}, author = {Chatterjee, Krishnendu and Henzinger, Thomas A and Ibsen-Jensen, Rasmus and Otop, Jan}, booktitle = {42nd International Colloquium}, isbn = {978-3-662-47665-9}, location = {Kyoto, Japan}, number = {Part II}, pages = {121 -- 133}, publisher = {Springer Nature}, title = {{Edit distance for pushdown automata}}, doi = {10.1007/978-3-662-47666-6_10}, volume = {9135}, year = {2015}, } @article{1624, abstract = {Population structure can facilitate evolution of cooperation. In a structured population, cooperators can form clusters which resist exploitation by defectors. Recently, it was observed that a shift update rule is an extremely strong amplifier of cooperation in a one dimensional spatial model. For the shift update rule, an individual is chosen for reproduction proportional to fecundity; the offspring is placed next to the parent; a random individual dies. Subsequently, the population is rearranged (shifted) until all individual cells are again evenly spaced out. For large population size and a one dimensional population structure, the shift update rule favors cooperation for any benefit-to-cost ratio greater than one. But every attempt to generalize shift updating to higher dimensions while maintaining its strong effect has failed. The reason is that in two dimensions the clusters are fragmented by the movements caused by rearranging the cells. Here we introduce the natural phenomenon of a repulsive force between cells of different types. After a birth and death event, the cells are being rearranged minimizing the overall energy expenditure. If the repulsive force is sufficiently high, shift becomes a strong promoter of cooperation in two dimensions.}, author = {Pavlogiannis, Andreas and Chatterjee, Krishnendu and Adlam, Ben and Nowak, Martin}, journal = {Scientific Reports}, publisher = {Nature Publishing Group}, title = {{Cellular cooperation with shift updating and repulsion}}, doi = {10.1038/srep17147}, volume = {5}, year = {2015}, } @inproceedings{1656, abstract = {Recently there has been a significant effort to handle quantitative properties in formal verification and synthesis. While weighted automata over finite and infinite words provide a natural and flexible framework to express quantitative properties, perhaps surprisingly, some basic system properties such as average response time cannot be expressed using weighted automata, nor in any other know decidable formalism. In this work, we introduce nested weighted automata as a natural extension of weighted automata which makes it possible to express important quantitative properties such as average response time. In nested weighted automata, a master automaton spins off and collects results from weighted slave automata, each of which computes a quantity along a finite portion of an infinite word. Nested weighted automata can be viewed as the quantitative analogue of monitor automata, which are used in run-time verification. We establish an almost complete decidability picture for the basic decision problems about nested weighted automata, and illustrate their applicability in several domains. In particular, nested weighted automata can be used to decide average response time properties.}, author = {Chatterjee, Krishnendu and Henzinger, Thomas A and Otop, Jan}, booktitle = {Proceedings - Symposium on Logic in Computer Science}, location = {Kyoto, Japan}, publisher = {IEEE}, title = {{Nested weighted automata}}, doi = {10.1109/LICS.2015.72}, volume = {2015-July}, year = {2015}, } @inproceedings{1657, abstract = {We consider Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) objectives. There exist two different views: (i) ~the expectation semantics, where the goal is to optimize the expected mean-payoff objective, and (ii) ~the satisfaction semantics, where the goal is to maximize the probability of runs such that the mean-payoff value stays above a given vector. We consider optimization with respect to both objectives at once, thus unifying the existing semantics. Precisely, the goal is to optimize the expectation while ensuring the satisfaction constraint. Our problem captures the notion of optimization with respect to strategies that are risk-averse (i.e., Ensure certain probabilistic guarantee). Our main results are as follows: First, we present algorithms for the decision problems, which are always polynomial in the size of the MDP. We also show that an approximation of the Pareto curve can be computed in time polynomial in the size of the MDP, and the approximation factor, but exponential in the number of dimensions. Second, we present a complete characterization of the strategy complexity (in terms of memory bounds and randomization) required to solve our problem. }, author = {Chatterjee, Krishnendu and Komárková, Zuzana and Kretinsky, Jan}, location = {Kyoto, Japan}, pages = {244 -- 256}, publisher = {IEEE}, title = {{Unifying two views on multiple mean-payoff objectives in Markov decision processes}}, doi = {10.1109/LICS.2015.32}, year = {2015}, } @inproceedings{1660, abstract = {We study the pattern frequency vector for runs in probabilistic Vector Addition Systems with States (pVASS). Intuitively, each configuration of a given pVASS is assigned one of finitely many patterns, and every run can thus be seen as an infinite sequence of these patterns. The pattern frequency vector assigns to each run the limit of pattern frequencies computed for longer and longer prefixes of the run. If the limit does not exist, then the vector is undefined. We show that for one-counter pVASS, the pattern frequency vector is defined and takes one of finitely many values for almost all runs. Further, these values and their associated probabilities can be approximated up to an arbitrarily small relative error in polynomial time. For stable two-counter pVASS, we show the same result, but we do not provide any upper complexity bound. As a byproduct of our study, we discover counterexamples falsifying some classical results about stochastic Petri nets published in the 80s.}, author = {Brázdil, Tomáš and Kiefer, Stefan and Kučera, Antonín and Novotny, Petr}, location = {Kyoto, Japan}, pages = {44 -- 55}, publisher = {IEEE}, title = {{Long-run average behaviour of probabilistic vector addition systems}}, doi = {10.1109/LICS.2015.15}, year = {2015}, } @inproceedings{1661, abstract = {The computation of the winning set for one-pair Streett objectives and for k-pair Streett objectives in (standard) graphs as well as in game graphs are central problems in computer-aided verification, with application to the verification of closed systems with strong fairness conditions, the verification of open systems, checking interface compatibility, well-formed ness of specifications, and the synthesis of reactive systems. We give faster algorithms for the computation of the winning set for (1) one-pair Streett objectives (aka parity-3 problem) in game graphs and (2) for k-pair Streett objectives in graphs. For both problems this represents the first improvement in asymptotic running time in 15 years.}, author = {Chatterjee, Krishnendu and Henzinger, Monika H and Loitzenbauer, Veronika}, booktitle = {Proceedings - Symposium on Logic in Computer Science}, location = {Kyoto, Japan}, publisher = {IEEE}, title = {{Improved algorithms for one-pair and k-pair Streett objectives}}, doi = {10.1109/LICS.2015.34}, volume = {2015-July}, year = {2015}, } @article{1665, abstract = {Which genetic alterations drive tumorigenesis and how they evolve over the course of disease and therapy are central questions in cancer biology. Here we identify 44 recurrently mutated genes and 11 recurrent somatic copy number variations through whole-exome sequencing of 538 chronic lymphocytic leukaemia (CLL) and matched germline DNA samples, 278 of which were collected in a prospective clinical trial. These include previously unrecognized putative cancer drivers (RPS15, IKZF3), and collectively identify RNA processing and export, MYC activity, and MAPK signalling as central pathways involved in CLL. Clonality analysis of this large data set further enabled reconstruction of temporal relationships between driver events. Direct comparison between matched pre-treatment and relapse samples from 59 patients demonstrated highly frequent clonal evolution. Thus, large sequencing data sets of clinically informative samples enable the discovery of novel genes associated with cancer, the network of relationships between the driver events, and their impact on disease relapse and clinical outcome.}, author = {Landau, Dan and Tausch, Eugen and Taylor Weiner, Amaro and Stewart, Chip and Reiter, Johannes and Bahlo, Jasmin and Kluth, Sandra and Božić, Ivana and Lawrence, Michael and Böttcher, Sebastian and Carter, Scott and Cibulskis, Kristian and Mertens, Daniel and Sougnez, Carrie and Rosenberg, Mara and Hess, Julian and Edelmann, Jennifer and Kless, Sabrina and Kneba, Michael and Ritgen, Matthias and Fink, Anna and Fischer, Kirsten and Gabriel, Stacey and Lander, Eric and Nowak, Martin and Döhner, Hartmut and Hallek, Michael and Neuberg, Donna and Getz, Gad and Stilgenbauer, Stephan and Wu, Catherine}, journal = {Nature}, number = {7574}, pages = {525 -- 530}, publisher = {Nature Publishing Group}, title = {{Mutations driving CLL and their evolution in progression and relapse}}, doi = {10.1038/nature15395}, volume = {526}, year = {2015}, } @inproceedings{1667, abstract = {We consider parametric version of fixed-delay continuoustime Markov chains (or equivalently deterministic and stochastic Petri nets, DSPN) where fixed-delay transitions are specified by parameters, rather than concrete values. Our goal is to synthesize values of these parameters that, for a given cost function, minimise expected total cost incurred before reaching a given set of target states. We show that under mild assumptions, optimal values of parameters can be effectively approximated using translation to a Markov decision process (MDP) whose actions correspond to discretized values of these parameters. To this end we identify and overcome several interesting phenomena arising in systems with fixed delays.}, author = {Brázdil, Tomáš and Korenčiak, L'Uboš and Krčál, Jan and Novotny, Petr and Řehák, Vojtěch}, location = {Madrid, Spain}, pages = {141 -- 159}, publisher = {Springer}, title = {{Optimizing performance of continuous-time stochastic systems using timeout synthesis}}, doi = {10.1007/978-3-319-22264-6_10}, volume = {9259}, year = {2015}, } @article{1673, abstract = {When a new mutant arises in a population, there is a probability it outcompetes the residents and fixes. The structure of the population can affect this fixation probability. Suppressing population structures reduce the difference between two competing variants, while amplifying population structures enhance the difference. Suppressors are ubiquitous and easy to construct, but amplifiers for the large population limit are more elusive and only a few examples have been discovered. Whether or not a population structure is an amplifier of selection depends on the probability distribution for the placement of the invading mutant. First, we prove that there exist only bounded amplifiers for adversarial placement-that is, for arbitrary initial conditions. Next, we show that the Star population structure, which is known to amplify for mutants placed uniformly at random, does not amplify for mutants that arise through reproduction and are therefore placed proportional to the temperatures of the vertices. Finally, we construct population structures that amplify for all mutational events that arise through reproduction, uniformly at random, or through some combination of the two. }, author = {Adlam, Ben and Chatterjee, Krishnendu and Nowak, Martin}, journal = {Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences}, number = {2181}, publisher = {Royal Society of London}, title = {{Amplifiers of selection}}, doi = {10.1098/rspa.2015.0114}, volume = {471}, year = {2015}, } @article{1681, abstract = {In many social situations, individuals endeavor to find the single best possible partner, but are constrained to evaluate the candidates in sequence. Examples include the search for mates, economic partnerships, or any other long-term ties where the choice to interact involves two parties. Surprisingly, however, previous theoretical work on mutual choice problems focuses on finding equilibrium solutions, while ignoring the evolutionary dynamics of decisions. Empirically, this may be of high importance, as some equilibrium solutions can never be reached unless the population undergoes radical changes and a sufficient number of individuals change their decisions simultaneously. To address this question, we apply a mutual choice sequential search problem in an evolutionary game-theoretical model that allows one to find solutions that are favored by evolution. As an example, we study the influence of sequential search on the evolutionary dynamics of cooperation. For this, we focus on the classic snowdrift game and the prisoner’s dilemma game.}, author = {Priklopil, Tadeas and Chatterjee, Krishnendu}, issn = {2073-4336}, journal = {Games}, number = {4}, pages = {413 -- 437}, publisher = {MDPI}, title = {{Evolution of decisions in population games with sequentially searching individuals}}, doi = {10.3390/g6040413}, volume = {6}, year = {2015}, } @inproceedings{1689, abstract = {We consider the problem of computing the set of initial states of a dynamical system such that there exists a control strategy to ensure that the trajectories satisfy a temporal logic specification with probability 1 (almost-surely). We focus on discrete-time, stochastic linear dynamics and specifications given as formulas of the Generalized Reactivity(1) fragment of Linear Temporal Logic over linear predicates in the states of the system. We propose a solution based on iterative abstraction-refinement, and turn-based 2-player probabilistic games. While the theoretical guarantee of our algorithm after any finite number of iterations is only a partial solution, we show that if our algorithm terminates, then the result is the set of satisfying initial states. Moreover, for any (partial) solution our algorithm synthesizes witness control strategies to ensure almost-sure satisfaction of the temporal logic specification. We demonstrate our approach on an illustrative case study.}, author = {Svoreňová, Mária and Kretinsky, Jan and Chmelik, Martin and Chatterjee, Krishnendu and Cěrná, Ivana and Belta, Cǎlin}, booktitle = {Proceedings of the 18th International Conference on Hybrid Systems: Computation and Control}, location = {Seattle, WA, United States}, pages = {259 -- 268}, publisher = {ACM}, title = {{Temporal logic control for stochastic linear systems using abstraction refinement of probabilistic games}}, doi = {10.1145/2728606.2728608}, year = {2015}, } @inproceedings{1691, abstract = {We consider a case study of the problem of deploying an autonomous air vehicle in a partially observable, dynamic, indoor environment from a specification given as a linear temporal logic (LTL) formula over regions of interest. We model the motion and sensing capabilities of the vehicle as a partially observable Markov decision process (POMDP). We adapt recent results for solving POMDPs with parity objectives to generate a control policy. We also extend the existing framework with a policy minimization technique to obtain a better implementable policy, while preserving its correctness. The proposed techniques are illustrated in an experimental setup involving an autonomous quadrotor performing surveillance in a dynamic environment.}, author = {Svoreňová, Mária and Chmelik, Martin and Leahy, Kevin and Eniser, Hasan and Chatterjee, Krishnendu and Cěrná, Ivana and Belta, Cǎlin}, booktitle = {Proceedings of the 18th International Conference on Hybrid Systems: Computation and Control}, location = {Seattle, WA, United States}, pages = {233 -- 238}, publisher = {ACM}, title = {{Temporal logic motion planning using POMDPs with parity objectives: Case study paper}}, doi = {10.1145/2728606.2728617}, year = {2015}, } @article{1694, abstract = { We introduce quantitative timed refinement and timed simulation (directed) metrics, incorporating zenoness checks, for timed systems. These metrics assign positive real numbers which quantify the timing mismatches between two timed systems, amongst non-zeno runs. We quantify timing mismatches in three ways: (1) the maximal timing mismatch that can arise, (2) the “steady-state” maximal timing mismatches, where initial transient timing mismatches are ignored; and (3) the (long-run) average timing mismatches amongst two systems. These three kinds of mismatches constitute three important types of timing differences. Our event times are the global times, measured from the start of the system execution, not just the time durations of individual steps. We present algorithms over timed automata for computing the three quantitative simulation distances to within any desired degree of accuracy. In order to compute the values of the quantitative simulation distances, we use a game theoretic formulation. We introduce two new kinds of objectives for two player games on finite-state game graphs: (1) eventual debit-sum level objectives, and (2) average debit-sum level objectives. We present algorithms for computing the optimal values for these objectives in graph games, and then use these algorithms to compute the values of the timed simulation distances over timed automata. }, author = {Chatterjee, Krishnendu and Prabhu, Vinayak}, journal = {IEEE Transactions on Automatic Control}, number = {9}, pages = {2291 -- 2306}, publisher = {IEEE}, title = {{Quantitative temporal simulation and refinement distances for timed systems}}, doi = {10.1109/TAC.2015.2404612}, volume = {60}, year = {2015}, } @article{1698, abstract = {In mean-payoff games, the objective of the protagonist is to ensure that the limit average of an infinite sequence of numeric weights is nonnegative. In energy games, the objective is to ensure that the running sum of weights is always nonnegative. Multi-mean-payoff and multi-energy games replace individual weights by tuples, and the limit average (resp., running sum) of each coordinate must be (resp., remain) nonnegative. We prove finite-memory determinacy of multi-energy games and show inter-reducibility of multi-mean-payoff and multi-energy games for finite-memory strategies. We improve the computational complexity for solving both classes with finite-memory strategies: we prove coNP-completeness improving the previous known EXPSPACE bound. For memoryless strategies, we show that deciding the existence of a winning strategy for the protagonist is NP-complete. We present the first solution of multi-mean-payoff games with infinite-memory strategies: we show that mean-payoff-sup objectives can be decided in NP∩coNP, whereas mean-payoff-inf objectives are coNP-complete.}, author = {Velner, Yaron and Chatterjee, Krishnendu and Doyen, Laurent and Henzinger, Thomas A and Rabinovich, Alexander and Raskin, Jean}, journal = {Information and Computation}, number = {4}, pages = {177 -- 196}, publisher = {Elsevier}, title = {{The complexity of multi-mean-payoff and multi-energy games}}, doi = {10.1016/j.ic.2015.03.001}, volume = {241}, year = {2015}, }