@misc{5549, abstract = {This repository contains the experimental part of the CAV 2015 publication Counterexample Explanation by Learning Small Strategies in Markov Decision Processes. We extended the probabilistic model checker PRISM to represent strategies of Markov Decision Processes as Decision Trees. The archive contains a java executable version of the extended tool (prism_dectree.jar) together with a few examples of the PRISM benchmark library. To execute the program, please have a look at the README.txt, which provides instructions and further information on the archive. The archive contains scripts that (if run often enough) reproduces the data presented in the publication.}, author = {Fellner, Andreas}, keywords = {Markov Decision Process, Decision Tree, Probabilistic Verification, Counterexample Explanation}, publisher = {Institute of Science and Technology Austria}, title = {{Experimental part of CAV 2015 publication: Counterexample Explanation by Learning Small Strategies in Markov Decision Processes}}, doi = {10.15479/AT:ISTA:28}, year = {2015}, } @inproceedings{10796, abstract = {We consider concurrent mean-payoff games, a very well-studied class of two-player (player 1 vs player 2) zero-sum games on finite-state graphs where every transition is assigned a reward between 0 and 1, and the payoff function is the long-run average of the rewards. The value is the maximal expected payoff that player 1 can guarantee against all strategies of player 2. We consider the computation of the set of states with value 1 under finite-memory strategies for player 1, and our main results for the problem are as follows: (1) we present a polynomial-time algorithm; (2) we show that whenever there is a finite-memory strategy, there is a stationary strategy that does not need memory at all; and (3) we present an optimal bound (which is double exponential) on the patience of stationary strategies (where patience of a distribution is the inverse of the smallest positive probability and represents a complexity measure of a stationary strategy).}, author = {Chatterjee, Krishnendu and Ibsen-Jensen, Rasmus}, booktitle = {Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms}, isbn = {978-161197374-7}, location = {San Diego, CA, United States}, number = {1}, pages = {1018--1029}, publisher = {SIAM}, title = {{The value 1 problem under finite-memory strategies for concurrent mean-payoff games}}, doi = {10.1137/1.9781611973730.69}, volume = {2015}, year = {2015}, } @article{1731, abstract = {We consider two-player zero-sum games on graphs. These games can be classified on the basis of the information of the players and on the mode of interaction between them. On the basis of information the classification is as follows: (a) partial-observation (both players have partial view of the game); (b) one-sided complete-observation (one player has complete observation); and (c) complete-observation (both players have complete view of the game). On the basis of mode of interaction we have the following classification: (a) concurrent (both players interact simultaneously); and (b) turn-based (both players interact in turn). The two sources of randomness in these games are randomness in transition function and randomness in strategies. In general, randomized strategies are more powerful than deterministic strategies, and randomness in transitions gives more general classes of games. In this work we present a complete characterization for the classes of games where randomness is not helpful in: (a) the transition function probabilistic transition can be simulated by deterministic transition); and (b) strategies (pure strategies are as powerful as randomized strategies). As consequence of our characterization we obtain new undecidability results for these games. }, author = {Chatterjee, Krishnendu and Doyen, Laurent and Gimbert, Hugo and Henzinger, Thomas A}, journal = {Information and Computation}, number = {12}, pages = {3 -- 16}, publisher = {Elsevier}, title = {{Randomness for free}}, doi = {10.1016/j.ic.2015.06.003}, volume = {245}, year = {2015}, } @inproceedings{1732, abstract = {We consider partially observable Markov decision processes (POMDPs), that are a standard framework for robotics applications to model uncertainties present in the real world, with temporal logic specifications. All temporal logic specifications in linear-time temporal logic (LTL) can be expressed as parity objectives. We study the qualitative analysis problem for POMDPs with parity objectives that asks whether there is a controller (policy) to ensure that the objective holds with probability 1 (almost-surely). While the qualitative analysis of POMDPs with parity objectives is undecidable, recent results show that when restricted to finite-memory policies the problem is EXPTIME-complete. While the problem is intractable in theory, we present a practical approach to solve the qualitative analysis problem. We designed several heuristics to deal with the exponential complexity, and have used our implementation on a number of well-known POMDP examples for robotics applications. Our results provide the first practical approach to solve the qualitative analysis of robot motion planning with LTL properties in the presence of uncertainty.}, author = {Chatterjee, Krishnendu and Chmelik, Martin and Gupta, Raghav and Kanodia, Ayush}, location = {Seattle, WA, United States}, pages = {325 -- 330}, publisher = {IEEE}, title = {{Qualitative analysis of POMDPs with temporal logic specifications for robotics applications}}, doi = {10.1109/ICRA.2015.7139019}, year = {2015}, } @inproceedings{1838, abstract = {Synthesis of program parts is particularly useful for concurrent systems. However, most approaches do not support common design tasks, like modifying a single process without having to re-synthesize or verify the whole system. Assume-guarantee synthesis (AGS) provides robustness against modifications of system parts, but thus far has been limited to the perfect information setting. This means that local variables cannot be hidden from other processes, which renders synthesis results cumbersome or even impossible to realize.We resolve this shortcoming by defining AGS under partial information. We analyze the complexity and decidability in different settings, showing that the problem has a high worstcase complexity and is undecidable in many interesting cases. Based on these observations, we present a pragmatic algorithm based on bounded synthesis, and demonstrate its practical applicability on several examples.}, author = {Bloem, Roderick and Chatterjee, Krishnendu and Jacobs, Swen and Könighofer, Robert}, location = {London, United Kingdom}, pages = {517 -- 532}, publisher = {Springer}, title = {{Assume-guarantee synthesis for concurrent reactive programs with partial information}}, doi = {10.1007/978-3-662-46681-0_50}, volume = {9035}, year = {2015}, } @inproceedings{1839, abstract = {We present MultiGain, a tool to synthesize strategies for Markov decision processes (MDPs) with multiple mean-payoff objectives. Our models are described in PRISM, and our tool uses the existing interface and simulator of PRISM. Our tool extends PRISM by adding novel algorithms for multiple mean-payoff objectives, and also provides features such as (i) generating strategies and exploring them for simulation, and checking them with respect to other properties; and (ii) generating an approximate Pareto curve for two mean-payoff objectives. In addition, we present a new practical algorithm for the analysis of MDPs with multiple mean-payoff objectives under memoryless strategies.}, author = {Brázdil, Tomáš and Chatterjee, Krishnendu and Forejt, Vojtěch and Kučera, Antonín}, location = {London, United Kingdom}, pages = {181 -- 187}, publisher = {Springer}, title = {{Multigain: A controller synthesis tool for MDPs with multiple mean-payoff objectives}}, doi = {10.1007/978-3-662-46681-0_12}, volume = {9035}, 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 on Automata, Languages, and Programming}, 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}, } @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}, } @misc{5435, abstract = {We consider Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) objectives. There have been 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 the problem where the goal is to optimize the expectation under the constraint that the satisfaction semantics is ensured, and thus consider a generalization that unifies the existing semantics. Our problem captures the notion of optimization with respect to strategies that are risk-averse (i.e., ensures certain probabilistic guarantee). Our main results are algorithms for the decision problem 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. Finally, 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 Komarkova, Zuzana and Kretinsky, Jan}, issn = {2664-1690}, pages = {51}, publisher = {IST Austria}, title = {{Unifying two views on multiple mean-payoff objectives in Markov decision processes}}, doi = {10.15479/AT:IST-2015-318-v2-1}, year = {2015}, } @misc{5429, abstract = {We consider Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) objectives. There have been 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 the problem where the goal is to optimize the expectation under the constraint that the satisfaction semantics is ensured, and thus consider a generalization that unifies the existing semantics. Our problem captures the notion of optimization with respect to strategies that are risk-averse (i.e., ensures certain probabilistic guarantee). Our main results are algorithms for the decision problem 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. Finally, 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 Komarkova, Zuzana and Kretinsky, Jan}, issn = {2664-1690}, pages = {41}, publisher = {IST Austria}, title = {{Unifying two views on multiple mean-payoff objectives in Markov decision processes}}, doi = {10.15479/AT:IST-2015-318-v1-1}, year = {2015}, } @misc{5438, 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 a pushdown automaton 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}, issn = {2664-1690}, pages = {15}, publisher = {IST Austria}, title = {{Edit distance for pushdown automata}}, doi = {10.15479/AT:IST-2015-334-v1-1}, 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{2034, abstract = {Opacity is a generic security property, that has been defined on (non-probabilistic) transition systems and later on Markov chains with labels. For a secret predicate, given as a subset of runs, and a function describing the view of an external observer, the value of interest for opacity is a measure of the set of runs disclosing the secret. We extend this definition to the richer framework of Markov decision processes, where non-deterministicchoice is combined with probabilistic transitions, and we study related decidability problems with partial or complete observation hypotheses for the schedulers. We prove that all questions are decidable with complete observation and ω-regular secrets. With partial observation, we prove that all quantitative questions are undecidable but the question whether a system is almost surely non-opaquebecomes decidable for a restricted class of ω-regular secrets, as well as for all ω-regular secrets under finite-memory schedulers.}, author = {Bérard, Béatrice and Chatterjee, Krishnendu and Sznajder, Nathalie}, journal = {Information Processing Letters}, number = {1}, pages = {52 -- 59}, publisher = {Elsevier}, title = {{Probabilistic opacity for Markov decision processes}}, doi = {10.1016/j.ipl.2014.09.001}, volume = {115}, 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}, } @misc{5436, 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}, issn = {2664-1690}, pages = {29}, publisher = {IST Austria}, title = {{Nested weighted automata}}, doi = {10.15479/AT:IST-2015-170-v2-2}, year = {2015}, } @article{1709, abstract = {The competition for resources among cells, individuals or species is a fundamental characteristic of evolution. Biological all-pay auctions have been used to model situations where multiple individuals compete for a single resource. However, in many situations multiple resources with various values exist and single reward auctions are not applicable. We generalize the model to multiple rewards and study the evolution of strategies. In biological all-pay auctions the bid of an individual corresponds to its strategy and is equivalent to its payment in the auction. The decreasingly ordered rewards are distributed according to the decreasingly ordered bids of the participating individuals. The reproductive success of an individual is proportional to its fitness given by the sum of the rewards won minus its payments. Hence, successful bidding strategies spread in the population. We find that the results for the multiple reward case are very different from the single reward case. While the mixed strategy equilibrium in the single reward case with more than two players consists of mostly low-bidding individuals, we show that the equilibrium can convert to many high-bidding individuals and a few low-bidding individuals in the multiple reward case. Some reward values lead to a specialization among the individuals where one subpopulation competes for the rewards and the other subpopulation largely avoids costly competitions. Whether the mixed strategy equilibrium is an evolutionarily stable strategy (ESS) depends on the specific values of the rewards.}, author = {Reiter, Johannes and Kanodia, Ayush and Gupta, Raghav and Nowak, Martin and Chatterjee, Krishnendu}, journal = {Proceedings of the Royal Society of London Series B Biological Sciences}, number = {1812}, publisher = {Royal Society}, title = {{Biological auctions with multiple rewards}}, doi = {10.1098/rspb.2015.1041}, volume = {282}, year = {2015}, } @phdthesis{1400, abstract = {Cancer results from an uncontrolled growth of abnormal cells. Sequentially accumulated genetic and epigenetic alterations decrease cell death and increase cell replication. We used mathematical models to quantify the effect of driver gene mutations. The recently developed targeted therapies can lead to dramatic regressions. However, in solid cancers, clinical responses are often short-lived because resistant cancer cells evolve. We estimated that approximately 50 different mutations can confer resistance to a typical targeted therapeutic agent. We find that resistant cells are likely to be present in expanded subclones before the start of the treatment. The dominant strategy to prevent the evolution of resistance is combination therapy. Our analytical results suggest that in most patients, dual therapy, but not monotherapy, can result in long-term disease control. However, long-term control can only occur if there are no possible mutations in the genome that can cause cross-resistance to both drugs. Furthermore, we showed that simultaneous therapy with two drugs is much more likely to result in long-term disease control than sequential therapy with the same drugs. To improve our understanding of the underlying subclonal evolution we reconstruct the evolutionary history of a patient's cancer from next-generation sequencing data of spatially-distinct DNA samples. Using a quantitative measure of genetic relatedness, we found that pancreatic cancers and their metastases demonstrated a higher level of relatedness than that expected for any two cells randomly taken from a normal tissue. This minimal amount of genetic divergence among advanced lesions indicates that genetic heterogeneity, when quantitatively defined, is not a fundamental feature of the natural history of untreated pancreatic cancers. Our newly developed, phylogenomic tool Treeomics finds evidence for seeding patterns of metastases and can directly be used to discover rules governing the evolution of solid malignancies to transform cancer into a more predictable disease.}, author = {Reiter, Johannes}, issn = {2663-337X}, pages = {183}, publisher = {Institute of Science and Technology Austria}, title = {{The subclonal evolution of cancer}}, year = {2015}, } @inproceedings{1820, abstract = {We consider partially observable Markov decision processes (POMDPs) with a set of target states and every transition is associated with an integer cost. The optimization objec- tive we study asks to minimize the expected total cost till the target set is reached, while ensuring that the target set is reached almost-surely (with probability 1). We show that for integer costs approximating the optimal cost is undecidable. For positive costs, our results are as follows: (i) we establish matching lower and upper bounds for the optimal cost and the bound is double exponential; (ii) we show that the problem of approximating the optimal cost is decidable and present ap- proximation algorithms developing on the existing algorithms for POMDPs with finite-horizon objectives. While the worst- case running time of our algorithm is double exponential, we present efficient stopping criteria for the algorithm and show experimentally that it performs well in many examples.}, author = {Chatterjee, Krishnendu and Chmelik, Martin and Gupta, Raghav and Kanodia, Ayush}, booktitle = {Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence }, location = {Austin, TX, USA}, pages = {3496--3502}, publisher = {AAAI Press}, title = {{Optimal cost almost-sure reachability in POMDPs}}, doi = {10.1609/aaai.v29i1.9683}, volume = {5}, year = {2015}, } @inproceedings{10884, abstract = {We revisit the parameterized model checking problem for token-passing systems and specifications in indexed CTL  ∗ \X. Emerson and Namjoshi (1995, 2003) have shown that parameterized model checking of indexed CTL  ∗ \X in uni-directional token rings can be reduced to checking rings up to some cutoff size. Clarke et al. (2004) have shown a similar result for general topologies and indexed LTL \X, provided processes cannot choose the directions for sending or receiving the token. We unify and substantially extend these results by systematically exploring fragments of indexed CTL  ∗ \X with respect to general topologies. For each fragment we establish whether a cutoff exists, and for some concrete topologies, such as rings, cliques and stars, we infer small cutoffs. Finally, we show that the problem becomes undecidable, and thus no cutoffs exist, if processes are allowed to choose the directions in which they send or from which they receive the token.}, author = {Aminof, Benjamin and Jacobs, Swen and Khalimov, Ayrat and Rubin, Sasha}, booktitle = {Verification, Model Checking, and Abstract Interpretation}, isbn = {9783642540127}, issn = {1611-3349}, location = {San Diego, CA, United States}, pages = {262--281}, publisher = {Springer Nature}, title = {{Parameterized model checking of token-passing systems}}, doi = {10.1007/978-3-642-54013-4_15}, volume = {8318}, year = {2014}, } @inproceedings{10885, abstract = {Two-player games on graphs provide the theoretical framework for many important problems such as reactive synthesis. While the traditional study of two-player zero-sum games has been extended to multi-player games with several notions of equilibria, they are decidable only for perfect-information games, whereas several applications require imperfect-information games. In this paper we propose a new notion of equilibria, called doomsday equilibria, which is a strategy profile such that all players satisfy their own objective, and if any coalition of players deviates and violates even one of the players objective, then the objective of every player is violated. We present algorithms and complexity results for deciding the existence of doomsday equilibria for various classes of ω-regular objectives, both for imperfect-information games, and for perfect-information games.We provide optimal complexity bounds for imperfect-information games, and in most cases for perfect-information games.}, author = {Chatterjee, Krishnendu and Doyen, Laurent and Filiot, Emmanuel and Raskin, Jean-François}, booktitle = {VMCAI 2014: Verification, Model Checking, and Abstract Interpretation}, isbn = {9783642540127}, issn = {1611-3349}, location = {San Diego, CA, United States}, pages = {78--97}, publisher = {Springer Nature}, title = {{Doomsday equilibria for omega-regular games}}, doi = {10.1007/978-3-642-54013-4_5}, volume = {8318}, year = {2014}, }