@inproceedings{3858,
abstract = {We consider two-player zero-sum games on graphs. On the basis of the information available to the players 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 com- plete view of the game). We survey the complexity results for the problem of de- ciding the winner in various classes of partial-observation games with ω-regular winning conditions specified as parity objectives. We present a reduction from the class of parity objectives that depend on sequence of states of the game to the sub-class of parity objectives that only depend on the sequence of observations. We also establish that partial-observation acyclic games are PSPACE-complete.},
author = {Chatterjee, Krishnendu and Doyen, Laurent},
location = {Yogyakarta, Indonesia},
pages = {1 -- 14},
publisher = {Springer},
title = {{The complexity of partial-observation parity games}},
doi = {10.1007/978-3-642-16242-8_1},
volume = {6397},
year = {2010},
}
@inproceedings{3860,
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. Generalized mean-payoff and energy games replace individual weights by tuples, and the limit average (resp. running sum) of each coordinate must be (resp. remain) nonnegative. These games have applications in the synthesis of resource-bounded processes with multiple resources. We prove the finite-memory determinacy of generalized energy games and show the inter- reducibility of generalized mean-payoff and energy games for finite-memory strategies. We also improve the computational complexity for solving both classes of games with finite-memory strategies: while the previously best known upper bound was EXPSPACE, and no lower bound was known, we give an optimal coNP-complete bound. For memoryless strategies, we show that the problem of deciding the existence of a winning strategy for the protagonist is NP-complete.},
author = {Chatterjee, Krishnendu and Doyen, Laurent and Henzinger, Thomas A and Raskin, Jean},
location = {Chennai, India},
pages = {505 -- 516},
publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik},
title = {{Generalized mean-payoff and energy games}},
doi = {10.4230/LIPIcs.FSTTCS.2010.505},
volume = {8},
year = {2010},
}
@inproceedings{3864,
abstract = {Often one has a preference order among the different systems that satisfy a given specification. Under a probabilistic assumption about the possible inputs, such a preference order is naturally expressed by a weighted automaton, which assigns to each word a value, such that a system is preferred if it generates a higher expected value. We solve the following optimal-synthesis problem: given an omega-regular specification, a Markov chain that describes the distribution of inputs, and a weighted automaton that measures how well a system satisfies the given specification tinder the given input assumption, synthesize a system that optimizes the measured value. For safety specifications and measures that are defined by mean-payoff automata, the optimal-synthesis problem amounts to finding a strategy in a Markov decision process (MDP) that is optimal for a long-run average reward objective, which can be done in polynomial time. For general omega-regular specifications, the solution rests on a new, polynomial-time algorithm for computing optimal strategies in MDPs with mean-payoff parity objectives. We present some experimental results showing optimal systems that were automatically generated in this way.},
author = {Chatterjee, Krishnendu and Henzinger, Thomas A and Jobstmann, Barbara and Singh, Rohit},
location = {Edinburgh, United Kingdom},
pages = {380 -- 395},
publisher = {Springer},
title = {{Measuring and synthesizing systems in probabilistic environments}},
doi = {10.1007/978-3-642-14295-6_34},
volume = {6174},
year = {2010},
}
@inproceedings{3866,
abstract = {Systems ought to behave reasonably even in circumstances that are not anticipated in their specifications. We propose a definition of robustness for liveness specifications which prescribes, for any number of environment assumptions that are violated, a minimal number of system guarantees that must still be fulfilled. This notion of robustness can be formulated and realized using a Generalized Reactivity formula. We present an algorithm for synthesizing robust systems from such formulas. For the important special case of Generalized Reactivity formulas of rank 1, our algorithm improves the complexity of [PPS06] for large specifications with a small number of assumptions and guarantees.},
author = {Bloem, Roderick and Chatterjee, Krishnendu and Greimel, Karin and Henzinger, Thomas A and Jobstmann, Barbara},
editor = {Touili, Tayssir and Cook, Byron and Jackson, Paul},
location = {Edinburgh, UK},
pages = {410 -- 424},
publisher = {Springer},
title = {{Robustness in the presence of liveness}},
doi = {10.1007/978-3-642-14295-6_36},
volume = {6174},
year = {2010},
}
@article{3862,
abstract = {Quantitative generalizations of classical languages, which assign to each word a real number instead of a Boolean value, have applications in modeling resource-constrained computation. We use weighted automata (finite automata with transition weights) to define several natural classes of quantitative languages over finite and infinite words; in particular, the real value of an infinite run is computed as the maximum, limsup, liminf, limit average, or discounted sum of the transition weights. We define the classical decision problems of automata theory (emptiness, universality, language inclusion, and language equivalence) in the quantitative setting and study their computational complexity. As the decidability of the language-inclusion problem remains open for some classes of weighted automata, we introduce a notion of quantitative simulation that is decidable and implies language inclusion. We also give a complete characterization of the expressive power of the various classes of weighted automata. In particular, we show that most classes of weighted automata cannot be determinized.},
author = {Chatterjee, Krishnendu and Doyen, Laurent and Henzinger, Thomas A},
journal = {ACM Transactions on Computational Logic (TOCL)},
number = {4},
publisher = {ACM},
title = {{Quantitative languages}},
doi = {10.1145/1805950.1805953},
volume = {11},
year = {2010},
}