@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},
}
@article{3128,
abstract = {We consider two-player zero-sum stochastic games on graphs with ω-regular winning conditions specified as parity objectives. These games have applications in the design and control of reactive systems. We survey the complexity results for the problem of deciding the winner in such games, and in classes of interest obtained as special cases, based on the information and the power of randomization available to the players, on the class of objectives and on the winning mode. On the basis of information, these games can be classified as follows: (a) partial-observation (both players have partial view of the game); (b) one-sided partial-observation (one player has partial-observation and the other player has complete-observation); and (c) complete-observation (both players have complete view of the game). The one-sided partial-observation games have two important subclasses: the one-player games, known as partial-observation Markov decision processes (POMDPs), and the blind one-player games, known as probabilistic automata. On the basis of randomization, (a) the players may not be allowed to use randomization (pure strategies), or (b) they may choose a probability distribution over actions but the actual random choice is external and not visible to the player (actions invisible), or (c) they may use full randomization. Finally, various classes of games are obtained by restricting the parity objective to a reachability, safety, Büchi, or coBüchi condition. We also consider several winning modes, such as sure-winning (i.e., all outcomes of a strategy have to satisfy the winning condition), almost-sure winning (i.e., winning with probability 1), limit-sure winning (i.e., winning with probability arbitrarily close to 1), and value-threshold winning (i.e., winning with probability at least ν, where ν is a given rational). },
author = {Chatterjee, Krishnendu and Doyen, Laurent and Henzinger, Thomas A},
journal = {Formal Methods in System Design},
number = {2},
pages = {268 -- 284},
publisher = {Springer},
title = {{A survey of partial-observation stochastic parity games}},
doi = {10.1007/s10703-012-0164-2},
volume = {43},
year = {2012},
}
@inproceedings{3135,
abstract = {We introduce consumption games, a model for discrete interactive system with multiple resources that are consumed or reloaded independently. More precisely, a consumption game is a finite-state graph where each transition is labeled by a vector of resource updates, where every update is a non-positive number or ω. The ω updates model the reloading of a given resource. Each vertex belongs either to player □ or player ◇, where the aim of player □ is to play so that the resources are never exhausted. We consider several natural algorithmic problems about consumption games, and show that although these problems are computationally hard in general, they are solvable in polynomial time for every fixed number of resource types (i.e., the dimension of the update vectors) and bounded resource updates. },
author = {Brázdil, Brázdil and Chatterjee, Krishnendu and Kučera, Antonín and Novotny, Petr},
location = {Berkeley, CA, USA},
pages = {23 -- 38},
publisher = {Springer},
title = {{Efficient controller synthesis for consumption games with multiple resource types}},
doi = {10.1007/978-3-642-31424-7_8},
volume = {7358},
year = {2012},
}
@article{3157,
abstract = {Colorectal tumours that are wild type for KRAS are often sensitive to EGFR blockade, but almost always develop resistance within several months of initiating therapy. The mechanisms underlying this acquired resistance to anti-EGFR antibodies are largely unknown. This situation is in marked contrast to that of small-molecule targeted agents, such as inhibitors of ABL, EGFR, BRAF and MEK, in which mutations in the genes encoding the protein targets render the tumours resistant to the effects of the drugs. The simplest hypothesis to account for the development of resistance to EGFR blockade is that rare cells with KRAS mutations pre-exist at low levels in tumours with ostensibly wild-type KRAS genes. Although this hypothesis would seem readily testable, there is no evidence in pre-clinical models to support it, nor is there data from patients. To test this hypothesis, we determined whether mutant KRAS DNA could be detected in the circulation of 28 patients receiving monotherapy with panitumumab, a therapeutic anti-EGFR antibody. We found that 9 out of 24 (38%) patients whose tumours were initially KRAS wild type developed detectable mutations in KRAS in their sera, three of which developed multiple different KRAS mutations. The appearance of these mutations was very consistent, generally occurring between 5 and 6months following treatment. Mathematical modelling indicated that the mutations were present in expanded subclones before the initiation of panitumumab treatment. These results suggest that the emergence of KRAS mutations is a mediator of acquired resistance to EGFR blockade and that these mutations can be detected in a non-invasive manner. They explain why solid tumours develop resistance to targeted therapies in a highly reproducible fashion.},
author = {Diaz Jr, Luis and Williams, Richard and Wu, Jian and Kinde, Isaac and Hecht, Joel and Berlin, Jordan and Allen, Benjamin and Božić, Ivana and Reiter, Johannes and Nowak, Martin and Kinzler, Kenneth and Oliner, Kelly and Vogelstein, Bert},
journal = {Nature},
number = {7404},
pages = {537 -- 540},
publisher = {Nature Publishing Group},
title = {{The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers}},
doi = {10.1038/nature11219},
volume = {486},
year = {2012},
}
@inproceedings{3165,
abstract = {Computing the winning set for Büchi objectives in alternating games on graphs is a central problem in computer aided verification with a large number of applications. The long standing best known upper bound for solving the problem is Õ(n·m), where n is the number of vertices and m is the number of edges in the graph. We are the first to break the Õ(n·m) boundary by presenting a new technique that reduces the running time to O(n 2). This bound also leads to O(n 2) time algorithms for computing the set of almost-sure winning vertices for Büchi objectives (1) in alternating games with probabilistic transitions (improving an earlier bound of Õ(n·m)), (2) in concurrent graph games with constant actions (improving an earlier bound of O(n 3)), and (3) in Markov decision processes (improving for m > n 4/3 an earlier bound of O(min(m 1.5, m·n 2/3)). We also show that the same technique can be used to compute the maximal end-component decomposition of a graph in time O(n 2), which is an improvement over earlier bounds for m > n 4/3. Finally, we show how to maintain the winning set for Büchi objectives in alternating games under a sequence of edge insertions or a sequence of edge deletions in O(n) amortized time per operation. This is the first dynamic algorithm for this problem.},
author = {Chatterjee, Krishnendu and Henzinger, Monika},
booktitle = {Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms},
location = {Kyoto, Japan},
pages = {1386 -- 1399},
publisher = {SIAM},
title = {{An O(n2) time algorithm for alternating Büchi games}},
doi = {10.1137/1.9781611973099.109},
year = {2012},
}
@inproceedings{3252,
abstract = {We study the automatic synthesis of fair non-repudiation protocols, a class of fair exchange protocols, used for digital contract signing. First, we show how to specify the objectives of the participating agents, the trusted third party (TTP) and the protocols as path formulas in Linear Temporal Logic (LTL) and prove that the satisfaction of the objectives of the agents and the TTP imply satisfaction of the protocol objectives. We then show that weak (co-operative) co-synthesis and classical (strictly competitive) co-synthesis fail in synthesizing these protocols, whereas assume-guarantee synthesis (AGS) succeeds. We demonstrate the success of assume-guarantee synthesis as follows: (a) any solution of assume-guarantee synthesis is attack-free; no subset of participants can violate the objectives of the other participants without violating their own objectives; (b) the Asokan-Shoup-Waidner (ASW) certified mail protocol that has known vulnerabilities is not a solution of AGS; and (c) the Kremer-Markowitch (KM) non-repudiation protocol is a solution of AGS. To our knowledge this is the first application of synthesis to fair non-repudiation protocols, and our results show how synthesis can generate correct protocols and automatically discover vulnerabilities. The solution to assume-guarantee synthesis can be computed efficiently as the secure equilibrium solution of three-player graph games. © 2012 Springer-Verlag.},
author = {Chatterjee, Krishnendu and Raman, Vishwanath},
location = {Philadelphia, PA, USA},
pages = {152 -- 168},
publisher = {Springer},
title = {{Synthesizing protocols for digital contract signing}},
doi = {10.1007/978-3-642-27940-9_11},
volume = {7148},
year = {2012},
}
@article{3254,
abstract = {The theory of graph games with ω-regular winning conditions is the foundation for modeling and synthesizing reactive processes. In the case of stochastic reactive processes, the corresponding stochastic graph games have three players, two of them (System and Environment) behaving adversarially, and the third (Uncertainty) behaving probabilistically. We consider two problems for stochastic graph games: the qualitative problem asks for the set of states from which a player can win with probability 1 (almost-sure winning); and the quantitative problem asks for the maximal probability of winning (optimal winning) from each state. We consider ω-regular winning conditions formalized as Müller winning conditions. We present optimal memory bounds for pure (deterministic) almost-sure winning and optimal winning strategies in stochastic graph games with Müller winning conditions. We also study the complexity of stochastic Müller games and show that both the qualitative and quantitative analysis problems are PSPACE-complete. Our results are relevant in synthesis of stochastic reactive processes.},
author = {Chatterjee, Krishnendu},
journal = {Information and Computation},
pages = {29 -- 48},
publisher = {Elsevier},
title = {{The complexity of stochastic Müller games}},
doi = {10.1016/j.ic.2011.11.004},
volume = {211},
year = {2012},
}
@inproceedings{3255,
abstract = {In this paper we survey results of two-player games on graphs and Markov decision processes with parity, mean-payoff and energy objectives, and the combination of mean-payoff and energy objectives with parity objectives. These problems have applications in verification and synthesis of reactive systems in resource-constrained environments.},
author = {Chatterjee, Krishnendu and Doyen, Laurent},
location = {Lednice, Czech Republic},
pages = {37 -- 46},
publisher = {Springer},
title = {{Games and Markov decision processes with mean payoff parity and energy parity objectives}},
doi = {10.1007/978-3-642-25929-6_3},
volume = {7119},
year = {2012},
}
@article{3260,
abstract = {Many scenarios in the living world, where individual organisms compete for winning positions (or resources), have properties of auctions. Here we study the evolution of bids in biological auctions. For each auction, n individuals are drawn at random from a population of size N. Each individual makes a bid which entails a cost. The winner obtains a benefit of a certain value. Costs and benefits are translated into reproductive success (fitness). Therefore, successful bidding strategies spread in the population. We compare two types of auctions. In “biological all-pay auctions”, the costs are the bid for every participating individual. In “biological second price all-pay auctions”, the cost for everyone other than the winner is the bid, but the cost for the winner is the second highest bid. Second price all-pay auctions are generalizations of the “war of attrition” introduced by Maynard Smith. We study evolutionary dynamics in both types of auctions. We calculate pairwise invasion plots and evolutionarily stable distributions over the continuous strategy space. We find that the average bid in second price all-pay auctions is higher than in all-pay auctions, but the average cost for the winner is similar in both auctions. In both cases, the average bid is a declining function of the number of participants, n. The more individuals participate in an auction the smaller is the chance of winning, and thus expensive bids must be avoided.
},
author = {Chatterjee, Krishnendu and Reiter, Johannes and Nowak, Martin},
journal = {Theoretical Population Biology},
number = {1},
pages = {69 -- 80},
publisher = {Academic Press},
title = {{Evolutionary dynamics of biological auctions}},
doi = {10.1016/j.tpb.2011.11.003},
volume = {81},
year = {2012},
}
@article{3314,
abstract = {We introduce two-level discounted and mean-payoff games played by two players on a perfect-information stochastic game graph. The upper level game is a discounted or mean-payoff game and the lower level game is a (undiscounted) reachability game. Two-level games model hierarchical and sequential decision making under uncertainty across different time scales. For both discounted and mean-payoff two-level games, we show the existence of pure memoryless optimal strategies for both players and an ordered field property. We show that if there is only one player (Markov decision processes), then the values can be computed in polynomial time. It follows that whether the value of a player is equal to a given rational constant in two-level discounted or mean-payoff games can be decided in NP ∩ coNP. We also give an alternate strategy improvement algorithm to compute the value. © 2012 World Scientific Publishing Company.},
author = {Chatterjee, Krishnendu and Majumdar, Ritankar},
journal = {International Journal of Foundations of Computer Science},
number = {3},
pages = {609 -- 625},
publisher = {World Scientific Publishing},
title = {{Discounting and averaging in games across time scales}},
doi = {10.1142/S0129054112400308},
volume = {23},
year = {2012},
}
@inproceedings{3341,
abstract = {We consider two-player stochastic games played on a finite state space for an infinite number of rounds. The games are concurrent: in each round, the two players (player 1 and player 2) choose their moves independently and simultaneously; the current state and the two moves determine a probability distribution over the successor states. We also consider the important special case of turn-based stochastic games where players make moves in turns, rather than concurrently. We study concurrent games with \omega-regular winning conditions specified as parity objectives. The value for player 1 for a parity objective is the maximal probability with which the player can guarantee the satisfaction of the objective against all strategies of the opponent. We study the problem of continuity and robustness of the value function in concurrent and turn-based stochastic parity gameswith respect to imprecision in the transition probabilities. We present quantitative bounds on the difference of the value function (in terms of the imprecision of the transition probabilities) and show the value continuity for structurally equivalent concurrent games (two games are structurally equivalent if the support of the transition function is same and the probabilities differ). We also show robustness of optimal strategies for structurally equivalent turn-based stochastic parity games. Finally we show that the value continuity property breaks without the structurally equivalent assumption (even for Markov chains) and show that our quantitative bound is asymptotically optimal. Hence our results are tight (the assumption is both necessary and sufficient) and optimal (our quantitative bound is asymptotically optimal).},
author = {Chatterjee, Krishnendu},
location = {Tallinn, Estonia},
pages = {270 -- 285},
publisher = {Springer},
title = {{Robustness of structurally equivalent concurrent parity games}},
doi = {10.1007/978-3-642-28729-9_18},
volume = {7213},
year = {2012},
}