@inproceedings{1374,
abstract = {We study two-player zero-sum games over infinite-state graphs equipped with ωB and finitary conditions. Our first contribution is about the strategy complexity, i.e the memory required for winning strategies: we prove that over general infinite-state graphs, memoryless strategies are sufficient for finitary Büchi, and finite-memory suffices for finitary parity games. We then study pushdown games with boundedness conditions, with two contributions. First we prove a collapse result for pushdown games with ωB-conditions, implying the decidability of solving these games. Second we consider pushdown games with finitary parity along with stack boundedness conditions, and show that solving these games is EXPTIME-complete.},
author = {Chatterjee, Krishnendu and Fijalkow, Nathanaël},
booktitle = {22nd EACSL Annual Conference on Computer Science Logic},
location = {Torino, Italy},
pages = {181 -- 196},
publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik},
title = {{Infinite-state games with finitary conditions}},
doi = {10.4230/LIPIcs.CSL.2013.181},
volume = {23},
year = {2013},
}
@inproceedings{1376,
abstract = {We consider the distributed synthesis problem for temporal logic specifications. Traditionally, the problem has been studied for LTL, and the previous results show that the problem is decidable iff there is no information fork in the architecture. We consider the problem for fragments of LTL and our main results are as follows: (1) We show that the problem is undecidable for architectures with information forks even for the fragment of LTL with temporal operators restricted to next and eventually. (2) For specifications restricted to globally along with non-nested next operators, we establish decidability (in EXPSPACE) for star architectures where the processes receive disjoint inputs, whereas we establish undecidability for architectures containing an information fork-meet structure. (3) Finally, we consider LTL without the next operator, and establish decidability (NEXPTIME-complete) for all architectures for a fragment that consists of a set of safety assumptions, and a set of guarantees where each guarantee is a safety, reachability, or liveness condition.},
author = {Chatterjee, Krishnendu and Henzinger, Thomas A and Otop, Jan and Pavlogiannis, Andreas},
booktitle = {13th International Conference on Formal Methods in Computer-Aided Design},
location = {Portland, OR, United States},
pages = {18 -- 25},
publisher = {IEEE},
title = {{Distributed synthesis for LTL fragments}},
doi = {10.1109/FMCAD.2013.6679386},
year = {2013},
}
@article{3116,
abstract = {Multithreaded programs coordinate their interaction through synchronization primitives like mutexes and semaphores, which are managed by an OS-provided resource manager. We propose algorithms for the automatic construction of code-aware resource managers for multithreaded embedded applications. Such managers use knowledge about the structure and resource usage (mutex and semaphore usage) of the threads to guarantee deadlock freedom and progress while managing resources in an efficient way. Our algorithms compute managers as winning strategies in certain infinite games, and produce a compact code description of these strategies. We have implemented the algorithms in the tool Cynthesis. Given a multithreaded program in C, the tool produces C code implementing a code-aware resource manager. We show in experiments that Cynthesis produces compact resource managers within a few minutes on a set of embedded benchmarks with up to 6 threads. © 2012 Springer Science+Business Media, LLC.},
author = {Chatterjee, Krishnendu and De Alfaro, Luca and Faella, Marco and Majumdar, Ritankar and Raman, Vishwanath},
journal = {Formal Methods in System Design},
number = {2},
pages = {142 -- 174},
publisher = {Springer},
title = {{Code aware resource management}},
doi = {10.1007/s10703-012-0170-4},
volume = {42},
year = {2013},
}
@article{2247,
abstract = {Cooperative behavior, where one individual incurs a cost to help another, is a wide spread phenomenon. Here we study direct reciprocity in the context of the alternating Prisoner's Dilemma. We consider all strategies that can be implemented by one and two-state automata. We calculate the payoff matrix of all pairwise encounters in the presence of noise. We explore deterministic selection dynamics with and without mutation. Using different error rates and payoff values, we observe convergence to a small number of distinct equilibria. Two of them are uncooperative strict Nash equilibria representing always-defect (ALLD) and Grim. The third equilibrium is mixed and represents a cooperative alliance of several strategies, dominated by a strategy which we call Forgiver. Forgiver cooperates whenever the opponent has cooperated; it defects once when the opponent has defected, but subsequently Forgiver attempts to re-establish cooperation even if the opponent has defected again. Forgiver is not an evolutionarily stable strategy, but the alliance, which it rules, is asymptotically stable. For a wide range of parameter values the most commonly observed outcome is convergence to the mixed equilibrium, dominated by Forgiver. Our results show that although forgiving might incur a short-term loss it can lead to a long-term gain. Forgiveness facilitates stable cooperation in the presence of exploitation and noise.},
author = {Zagorsky, Benjamin and Reiter, Johannes and Chatterjee, Krishnendu and Nowak, Martin},
journal = {PLoS One},
number = {12},
publisher = {Public Library of Science},
title = {{Forgiver triumphs in alternating prisoner's dilemma }},
doi = {10.1371/journal.pone.0080814},
volume = {8},
year = {2013},
}
@misc{9749,
abstract = {Cooperative behavior, where one individual incurs a cost to help another, is a wide spread phenomenon. Here we study direct reciprocity in the context of the alternating Prisoner's Dilemma. We consider all strategies that can be implemented by one and two-state automata. We calculate the payoff matrix of all pairwise encounters in the presence of noise. We explore deterministic selection dynamics with and without mutation. Using different error rates and payoff values, we observe convergence to a small number of distinct equilibria. Two of them are uncooperative strict Nash equilibria representing always-defect (ALLD) and Grim. The third equilibrium is mixed and represents a cooperative alliance of several strategies, dominated by a strategy which we call Forgiver. Forgiver cooperates whenever the opponent has cooperated; it defects once when the opponent has defected, but subsequently Forgiver attempts to re-establish cooperation even if the opponent has defected again. Forgiver is not an evolutionarily stable strategy, but the alliance, which it rules, is asymptotically stable. For a wide range of parameter values the most commonly observed outcome is convergence to the mixed equilibrium, dominated by Forgiver. Our results show that although forgiving might incur a short-term loss it can lead to a long-term gain. Forgiveness facilitates stable cooperation in the presence of exploitation and noise.},
author = {Zagorsky, Benjamin and Reiter, Johannes and Chatterjee, Krishnendu and Nowak, Martin},
publisher = {Public Library of Science},
title = {{Forgiver triumphs in alternating prisoner's dilemma }},
doi = {10.1371/journal.pone.0080814.s001},
year = {2013},
}
@inproceedings{2715,
abstract = {We consider Markov decision processes (MDPs) with specifications given as Büchi (liveness) objectives. We consider the problem of computing the set of almost-sure winning vertices from where the objective can be ensured with probability 1. We study for the first time the average case complexity of the classical algorithm for computing the set of almost-sure winning vertices for MDPs with Büchi objectives. Our contributions are as follows: First, we show that for MDPs with constant out-degree the expected number of iterations is at most logarithmic and the average case running time is linear (as compared to the worst case linear number of iterations and quadratic time complexity). Second, for the average case analysis over all MDPs we show that the expected number of iterations is constant and the average case running time is linear (again as compared to the worst case linear number of iterations and quadratic time complexity). Finally we also show that given that all MDPs are equally likely, the probability that the classical algorithm requires more than constant number of iterations is exponentially small.},
author = {Chatterjee, Krishnendu and Joglekar, Manas and Shah, Nisarg},
location = {Hyderabad, India},
pages = {461 -- 473},
publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik},
title = {{Average case analysis of the classical algorithm for Markov decision processes with Büchi objectives}},
doi = {10.4230/LIPIcs.FSTTCS.2012.461},
volume = {18},
year = {2012},
}
@article{2848,
abstract = {We study evolutionary game theory in a setting where individuals learn from each other. We extend the traditional approach by assuming that a population contains individuals with different learning abilities. In particular, we explore the situation where individuals have different search spaces, when attempting to learn the strategies of others. The search space of an individual specifies the set of strategies learnable by that individual. The search space is genetically given and does not change under social evolutionary dynamics. We introduce a general framework and study a specific example in the context of direct reciprocity. For this example, we obtain the counter intuitive result that cooperation can only evolve for intermediate benefit-to-cost ratios, while small and large benefit-to-cost ratios favor defection. Our paper is a step toward making a connection between computational learning theory and evolutionary game dynamics.},
author = {Chatterjee, Krishnendu and Zufferey, Damien and Nowak, Martin},
journal = {Journal of Theoretical Biology},
pages = {161 -- 173},
publisher = {Elsevier},
title = {{Evolutionary game dynamics in populations with different learners}},
doi = {10.1016/j.jtbi.2012.02.021},
volume = {301},
year = {2012},
}
@inproceedings{2916,
abstract = {The classical (boolean) notion of refinement for behavioral interfaces of system components is the alternating refinement preorder. In this paper, we define a quantitative measure for interfaces, called interface simulation distance. It makes the alternating refinement preorder quantitative by, intu- itively, tolerating errors (while counting them) in the alternating simulation game. We show that the interface simulation distance satisfies the triangle inequality, that the distance between two interfaces does not increase under parallel composition with a third interface, and that the distance between two interfaces can be bounded from above and below by distances between abstractions of the two interfaces. We illustrate the framework, and the properties of the distances under composition of interfaces, with two case studies.},
author = {Cerny, Pavol and Chmelik, Martin and Henzinger, Thomas A and Radhakrishna, Arjun},
booktitle = {Electronic Proceedings in Theoretical Computer Science},
location = {Napoli, Italy},
pages = {29 -- 42},
publisher = {EPTCS},
title = {{Interface Simulation Distances}},
doi = {10.4204/EPTCS.96.3},
volume = {96},
year = {2012},
}
@inproceedings{2936,
abstract = {The notion of delays arises naturally in many computational models, such as, in the design of circuits, control systems, and dataflow languages. In this work, we introduce automata with delay blocks (ADBs), extending finite state automata with variable time delay blocks, for deferring individual transition output symbols, in a discrete-time setting. We show that the ADB languages strictly subsume the regular languages, and are incomparable in expressive power to the context-free languages. We show that ADBs are closed under union, concatenation and Kleene star, and under intersection with regular languages, but not closed under complementation and intersection with other ADB languages. We show that the emptiness and the membership problems are decidable in polynomial time for ADBs, whereas the universality problem is undecidable. Finally we consider the linear-time model checking problem, i.e., whether the language of an ADB is contained in a regular language, and show that the model checking problem is PSPACE-complete. Copyright 2012 ACM.},
author = {Chatterjee, Krishnendu and Henzinger, Thomas A and Prabhu, Vinayak},
booktitle = {roceedings of the tenth ACM international conference on Embedded software},
location = {Tampere, Finland},
pages = {43 -- 52},
publisher = {ACM},
title = {{Finite automata with time delay blocks}},
doi = {10.1145/2380356.2380370},
year = {2012},
}
@inproceedings{2947,
abstract = {We introduce games with probabilistic uncertainty, a model for controller synthesis in which the controller observes the state through imprecise sensors that provide correct information about the current state with a fixed probability. That is, in each step, the sensors return an observed state, and given the observed state, there is a probability distribution (due to the estimation error) over the actual current state. The controller must base its decision on the observed state (rather than the actual current state, which it does not know). On the other hand, we assume that the environment can perfectly observe the current state. We show that controller synthesis for qualitative ω-regular objectives in our model can be reduced in polynomial time to standard partial-observation stochastic games, and vice-versa. As a consequence we establish the precise decidability frontier for the new class of games, and establish optimal complexity results for all the decidable problems.},
author = {Chatterjee, Krishnendu and Chmelik, Martin and Majumdar, Ritankar},
location = {Thiruvananthapuram, India},
pages = {385 -- 399},
publisher = {Springer},
title = {{Equivalence of games with probabilistic uncertainty and partial observation games}},
doi = {10.1007/978-3-642-33386-6_30},
volume = {7561},
year = {2012},
}
@inproceedings{2955,
abstract = {We consider two-player stochastic games played on finite graphs with reachability objectives where the first player tries to ensure a target state to be visited almost-surely (i.e., with probability 1), or positively (i.e., with positive probability), no matter the strategy of the second player. We classify such games according to the information and the power of randomization available to the players. On the basis of information, the game can be one-sided with either (a) player 1, or (b) player 2 having partial observation (and the other player has perfect observation), or two-sided with (c) both players having partial observation. On the basis of randomization, the players (a) may not be allowed to use randomization (pure strategies), or (b) may choose a probability distribution over actions but the actual random choice is external and not visible to the player (actions invisible), or (c) may use full randomization. Our main results for pure strategies are as follows. (1) For one-sided games with player 1 having partial observation we show that (in contrast to full randomized strategies) belief-based (subset-construction based) strategies are not sufficient, and we present an exponential upper bound on memory both for almostsure and positive winning strategies; we show that the problem of deciding the existence of almost-sure and positive winning strategies for player 1 is EXPTIME-complete. (2) For one-sided games with player 2 having partial observation we show that non-elementary memory is both necessary and sufficient for both almost-sure and positive winning strategies. (3) We show that for the general (two-sided) case finite-memory strategies are sufficient for both positive and almost-sure winning, and at least non-elementary memory is required. We establish the equivalence of the almost-sure winning problems for pure strategies and for randomized strategies with actions invisible. Our equivalence result exhibits serious flaws in previous results of the literature: we show a non-elementary memory lower bound for almost-sure winning whereas an exponential upper bound was previously claimed.},
author = {Chatterjee, Krishnendu and Doyen, Laurent},
booktitle = {Proceedings of the 2012 27th Annual ACM/IEEE Symposium on Logic in Computer Science},
location = {Dubrovnik, Croatia},
publisher = {IEEE},
title = {{Partial-observation stochastic games: How to win when belief fails}},
doi = {10.1109/LICS.2012.28},
year = {2012},
}
@inproceedings{2956,
abstract = {Two-player games on graphs are central in many problems in formal verification and program analysis such as synthesis and verification of open systems. In this work we consider solving recursive game graphs (or pushdown game graphs) that can model the control flow of sequential programs with recursion. While pushdown games have been studied before with qualitative objectives, such as reachability and parity objectives, in this work we study for the first time such games with the most well-studied quantitative objective, namely, mean payoff objectives. In pushdown games two types of strategies are relevant: (1) global strategies, that depend on the entire global history; and (2) modular strategies, that have only local memory and thus do not depend on the context of invocation, but only on the history of the current invocation of the module. Our main results are as follows: (1) One-player pushdown games with mean-payoff objectives under global strategies are decidable in polynomial time. (2) Two-player pushdown games with mean-payoff objectives under global strategies are undecidable. (3) One-player pushdown games with mean-payoff objectives under modular strategies are NP-hard. (4) Two-player pushdown games with mean-payoff objectives under modular strategies can be solved in NP (i.e., both one-player and two-player pushdown games with mean-payoff objectives under modular strategies are NP-complete). We also establish the optimal strategy complexity showing that global strategies for mean-payoff objectives require infinite memory even in one-player pushdown games; and memoryless modular strategies are sufficient in two-player pushdown games. Finally we also show that all the problems have the same computational complexity if the stack boundedness condition is added, where along with the mean-payoff objective the player must also ensure that the stack height is bounded.},
author = {Chatterjee, Krishnendu and Velner, Yaron},
booktitle = {Proceedings of the 2012 27th Annual ACM/IEEE Symposium on Logic in Computer Science},
location = {Dubrovnik, Croatia },
publisher = {IEEE},
title = {{Mean payoff pushdown games}},
doi = {10.1109/LICS.2012.30},
year = {2012},
}
@inproceedings{2957,
abstract = {We consider probabilistic automata on infinite words with acceptance defined by parity conditions. We consider three qualitative decision problems: (i) the positive decision problem asks whether there is a word that is accepted with positive probability; (ii) the almost decision problem asks whether there is a word that is accepted with probability 1; and (iii) the limit decision problem asks whether words are accepted with probability arbitrarily close to 1. We unify and generalize several decidability results for probabilistic automata over infinite words, and identify a robust (closed under union and intersection) subclass of probabilistic automata for which all the qualitative decision problems are decidable for parity conditions. We also show that if the input words are restricted to lasso shape (regular) words, then the positive and almost problems are decidable for all probabilistic automata with parity conditions. For most decidable problems we show an optimal PSPACE-complete complexity bound.},
author = {Chatterjee, Krishnendu and Tracol, Mathieu},
booktitle = {Proceedings of the 2012 27th Annual ACM/IEEE Symposium on Logic in Computer Science},
location = {Dubrovnik, Croatia },
publisher = {IEEE},
title = {{Decidable problems for probabilistic automata on infinite words}},
doi = {10.1109/LICS.2012.29},
year = {2012},
}
@article{2972,
abstract = {Energy parity games are infinite two-player turn-based games played on weighted graphs. The objective of the game combines a (qualitative) parity condition with the (quantitative) requirement that the sum of the weights (i.e., the level of energy in the game) must remain positive. Beside their own interest in the design and synthesis of resource-constrained omega-regular specifications, energy parity games provide one of the simplest model of games with combined qualitative and quantitative objectives. Our main results are as follows: (a) exponential memory is sufficient and may be necessary for winning strategies in energy parity games; (b) the problem of deciding the winner in energy parity games can be solved in NP ∩ coNP; and (c) we give an algorithm to solve energy parity by reduction to energy games. We also show that the problem of deciding the winner in energy parity games is logspace-equivalent to the problem of deciding the winner in mean-payoff parity games, which can thus be solved in NP ∩ coNP. As a consequence we also obtain a conceptually simple algorithm to solve mean-payoff parity games.},
author = {Chatterjee, Krishnendu and Doyen, Laurent},
journal = {Theoretical Computer Science},
pages = {49 -- 60},
publisher = {Elsevier},
title = {{Energy parity games}},
doi = {10.1016/j.tcs.2012.07.038},
volume = {458},
year = {2012},
}
@inproceedings{495,
abstract = {An automaton with advice is a finite state automaton which has access to an additional fixed infinite string called an advice tape. We refine the Myhill-Nerode theorem to characterize the languages of finite strings that are accepted by automata with advice. We do the same for tree automata with advice.},
author = {Kruckman, Alex and Rubin, Sasha and Sheridan, John and Zax, Ben},
booktitle = {Proceedings GandALF 2012},
location = {Napoli, Italy},
pages = {238 -- 246},
publisher = {Open Publishing Association},
title = {{A Myhill Nerode theorem for automata with advice}},
doi = {10.4204/EPTCS.96.18},
volume = {96},
year = {2012},
}
@inproceedings{496,
abstract = {We study the expressive power of logical interpretations on the class of scattered trees, namely those with countably many infinite branches. Scattered trees can be thought of as the tree analogue of scattered linear orders. Every scattered tree has an ordinal rank that reflects the structure of its infinite branches. We prove, roughly, that trees and orders of large rank cannot be interpreted in scattered trees of small rank. We consider a quite general notion of interpretation: each element of the interpreted structure is represented by a set of tuples of subsets of the interpreting tree. Our trees are countable, not necessarily finitely branching, and may have finitely many unary predicates as labellings. We also show how to replace injective set-interpretations in (not necessarily scattered) trees by 'finitary' set-interpretations.},
author = {Rabinovich, Alexander and Rubin, Sasha},
location = {Dubrovnik, Croatia},
publisher = {IEEE},
title = {{Interpretations in trees with countably many branches}},
doi = {10.1109/LICS.2012.65},
year = {2012},
}
@inproceedings{497,
abstract = {One central issue in the formal design and analysis of reactive systems is the notion of refinement that asks whether all behaviors of the implementation is allowed by the specification. The local interpretation of behavior leads to the notion of simulation. Alternating transition systems (ATSs) provide a general model for composite reactive systems, and the simulation relation for ATSs is known as alternating simulation. The simulation relation for fair transition systems is called fair simulation. In this work our main contributions are as follows: (1) We present an improved algorithm for fair simulation with Büchi fairness constraints; our algorithm requires O(n 3·m) time as compared to the previous known O(n 6)-time algorithm, where n is the number of states and m is the number of transitions. (2) We present a game based algorithm for alternating simulation that requires O(m2)-time as compared to the previous known O((n·m)2)-time algorithm, where n is the number of states and m is the size of transition relation. (3) We present an iterative algorithm for alternating simulation that matches the time complexity of the game based algorithm, but is more space efficient than the game based algorithm. © Krishnendu Chatterjee, Siddhesh Chaubal, and Pritish Kamath.},
author = {Chatterjee, Krishnendu and Chaubal, Siddhesh and Kamath, Pritish},
location = {Fontainebleau, France},
pages = {167 -- 182},
publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik},
title = {{Faster algorithms for alternating refinement relations}},
doi = {10.4230/LIPIcs.CSL.2012.167},
volume = {16},
year = {2012},
}
@misc{5377,
abstract = {Two-player games on graphs are central in many problems in formal verification and program analysis such as synthesis and verification of open systems. In this work we consider solving recursive game graphs (or pushdown game graphs) that can model the control flow of sequential programs with recursion. While pushdown games have been studied before with qualitative objectives, such as reachability and ω-regular objectives, in this work we study for the first time such games with the most well-studied quantitative objective, namely, mean-payoff objectives. In pushdown games two types of strategies are relevant: (1) global strategies, that depend on the entire global history; and (2) modular strategies, that have only local memory and thus do not depend on the context of invocation, but only on the history of the current invocation of the module. Our main results are as follows: (1) One-player pushdown games with mean-payoff objectives under global strategies are decidable in polynomial time. (2) Two- player pushdown games with mean-payoff objectives under global strategies are undecidable. (3) One-player pushdown games with mean-payoff objectives under modular strategies are NP- hard. (4) Two-player pushdown games with mean-payoff objectives under modular strategies can be solved in NP (i.e., both one-player and two-player pushdown games with mean-payoff objectives under modular strategies are NP-complete). We also establish the optimal strategy complexity showing that global strategies for mean-payoff objectives require infinite memory even in one-player pushdown games; and memoryless modular strategies are sufficient in two- player pushdown games. Finally we also show that all the problems have the same complexity if the stack boundedness condition is added, where along with the mean-payoff objective the player must also ensure that the stack height is bounded.},
author = {Chatterjee, Krishnendu and Velner, Yaron},
issn = {2664-1690},
pages = {33},
publisher = {IST Austria},
title = {{Mean-payoff pushdown games}},
doi = {10.15479/AT:IST-2012-0002},
year = {2012},
}
@misc{5378,
abstract = {One central issue in the formal design and analysis of reactive systems is the notion of refinement that asks whether all behaviors of the implementation is allowed by the specification. The local interpretation of behavior leads to the notion of simulation. Alternating transition systems (ATSs) provide a general model for composite reactive systems, and the simulation relation for ATSs is known as alternating simulation. The simulation relation for fair transition systems is called fair simulation. In this work our main contributions are as follows: (1) We present an improved algorithm for fair simulation with Büchi fairness constraints; our algorithm requires O(n3 · m) time as compared to the previous known O(n6)-time algorithm, where n is the number of states and m is the number of transitions. (2) We present a game based algorithm for alternating simulation that requires O(m2)-time as compared to the previous known O((n · m)2)-time algorithm, where n is the number of states and m is the size of transition relation. (3) We present an iterative algorithm for alternating simulation that matches the time complexity of the game based algorithm, but is more space efficient than the game based algorithm.},
author = {Chatterjee, Krishnendu and Chaubal, Siddhesh and Kamath, Pritish},
issn = {2664-1690},
pages = {21},
publisher = {IST Austria},
title = {{Faster algorithms for alternating refinement relations}},
doi = {10.15479/AT:IST-2012-0001},
year = {2012},
}
@article{3846,
abstract = {We summarize classical and recent results about two-player games played on graphs with ω-regular objectives. These games have applications in the verification and synthesis of reactive systems. Important distinctions are whether a graph game is turn-based or concurrent; deterministic or stochastic; zero-sum or not. We cluster known results and open problems according to these classifications.},
author = {Chatterjee, Krishnendu and Henzinger, Thomas A},
journal = {Journal of Computer and System Sciences},
number = {2},
pages = {394 -- 413},
publisher = {Elsevier},
title = {{A survey of stochastic ω regular games}},
doi = {10.1016/j.jcss.2011.05.002},
volume = {78},
year = {2012},
}