@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},
}
@article{3863,
abstract = {We consider two-player parity games with imperfect information in which strategies rely on observations that provide imperfect information about the history of a play. To solve such games, i.e., to determine the winning regions of players and corresponding winning strategies, one can use the subset construction to build an equivalent perfect-information game. Recently, an algorithm that avoids the inefficient subset construction has been proposed. The algorithm performs a fixed-point computation in a lattice of antichains, thus maintaining a succinct representation of state sets. However, this representation does not allow to recover winning strategies. In this paper, we build on the antichain approach to develop an algorithm for constructing the winning strategies in parity games of imperfect information. One major obstacle in adapting the classical procedure is that the complementation of attractor sets would break the invariant of downward-closedness on which the antichain representation relies. We overcome this difficulty by decomposing problem instances recursively into games with a combination of reachability, safety, and simpler parity conditions. We also report on an experimental implementation of our algorithm: to our knowledge, this is the first implementation of a procedure for solving imperfect-information parity games on graphs.},
author = {Berwanger, Dietmar and Chatterjee, Krishnendu and De Wulf, Martin and Doyen, Laurent and Henzinger, Thomas A},
journal = {Information and Computation},
number = {10},
pages = {1206 -- 1220},
publisher = {Elsevier},
title = {{Strategy construction for parity games with imperfect information}},
doi = {10.1016/j.ic.2009.09.006},
volume = {208},
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{3867,
abstract = {Weighted automata are nondeterministic automata with numerical weights on transitions. They can define quantitative languages L that assign to each word w a real number L(w). In the case of infinite words, the value of a run is naturally computed as the maximum, limsup, liminf, limit-average, or discounted-sum of the transition weights. The value of a word w is the supremum of the values of the runs over w. We study expressiveness and closure questions about these quantitative languages. We first show that the set of words with value greater than a threshold can be omega-regular for deterministic limit-average and discounted-sum automata, while this set is always omega-regular when the threshold is isolated (i.e., some neighborhood around the threshold contains no word). In the latter case, we prove that the omega-regular language is robust against small perturbations of the transition weights. We next consider automata with transition weights 0 or 1 and show that they are as expressive as general weighted automata in the limit-average case, but not in the discounted-sum case. Third, for quantitative languages L-1 and L-2, we consider the operations max(L-1, L-2), min(L-1, L-2), and 1 - L-1, which generalize the boolean operations on languages, as well as the sum L-1 + L-2. We establish the closure properties of all classes of quantitative languages with respect to these four operations.},
author = {Chatterjee, Krishnendu and Doyen, Laurent and Henzinger, Thomas A},
journal = {Logical Methods in Computer Science},
number = {3},
pages = {1 -- 23},
publisher = {International Federation of Computational Logic},
title = {{Expressiveness and closure properties for quantitative languages}},
doi = {10.2168/LMCS-6(3:10)2010},
volume = {6},
year = {2010},
}