@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{3129,
abstract = {Let K be a simplicial complex and g the rank of its p-th homology group Hp(K) defined with ℤ2 coefficients. We show that we can compute a basis H of Hp(K) and annotate each p-simplex of K with a binary vector of length g with the following property: the annotations, summed over all p-simplices in any p-cycle z, provide the coordinate vector of the homology class [z] in the basis H. The basis and the annotations for all simplices can be computed in O(n ω ) time, where n is the size of K and ω < 2.376 is a quantity so that two n×n matrices can be multiplied in O(n ω ) time. The precomputed annotations permit answering queries about the independence or the triviality of p-cycles efficiently.
Using annotations of edges in 2-complexes, we derive better algorithms for computing optimal basis and optimal homologous cycles in 1 - dimensional homology. Specifically, for computing an optimal basis of H1(K) , we improve the previously known time complexity from O(n 4) to O(n ω + n 2 g ω − 1). Here n denotes the size of the 2-skeleton of K and g the rank of H1(K) . Computing an optimal cycle homologous to a given 1-cycle is NP-hard even for surfaces and an algorithm taking 2 O(g) nlogn time is known for surfaces. We extend this algorithm to work with arbitrary 2-complexes in O(n ω ) + 2 O(g) n 2logn time using annotations.
},
author = {Busaryev, Oleksiy and Cabello, Sergio and Chen, Chao and Dey, Tamal and Wang, Yusu},
location = {Helsinki, Finland},
pages = {189 -- 200},
publisher = {Springer},
title = {{Annotating simplices with a homology basis and its applications}},
doi = {10.1007/978-3-642-31155-0_17},
volume = {7357},
year = {2012},
}
@inproceedings{3134,
abstract = {It has been an open question whether the sum of finitely many isotropic Gaussian kernels in n ≥ 2 dimensions can have more modes than kernels, until in 2003 Carreira-Perpiñán and Williams exhibited n +1 isotropic Gaussian kernels in ℝ n with n + 2 modes. We give a detailed analysis of this example, showing that it has exponentially many critical points and that the resilience of the extra mode grows like √n. In addition, we exhibit finite configurations of isotropic Gaussian kernels with superlinearly many modes. },
author = {Edelsbrunner, Herbert and Fasy, Brittany and Rote, Günter},
booktitle = {Proceedings of the twenty-eighth annual symposium on Computational geometry },
location = {Chapel Hill, NC, USA},
pages = {91 -- 100},
publisher = {ACM},
title = {{Add isotropic Gaussian kernels at own risk: More and more resilient modes in higher dimensions}},
doi = {10.1145/2261250.2261265},
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},
}
@inproceedings{3136,
abstract = {Continuous-time Markov chains (CTMC) with their rich theory and efficient simulation algorithms have been successfully used in modeling stochastic processes in diverse areas such as computer science, physics, and biology. However, systems that comprise non-instantaneous events cannot be accurately and efficiently modeled with CTMCs. In this paper we define delayed CTMCs, an extension of CTMCs that allows for the specification of a lower bound on the time interval between an event's initiation and its completion, and we propose an algorithm for the computation of their behavior. Our algorithm effectively decomposes the computation into two stages: a pure CTMC governs event initiations while a deterministic process guarantees lower bounds on event completion times. Furthermore, from the nature of delayed CTMCs, we obtain a parallelized version of our algorithm. We use our formalism to model genetic regulatory circuits (biological systems where delayed events are common) and report on the results of our numerical algorithm as run on a cluster. We compare performance and accuracy of our results with results obtained by using pure CTMCs. © 2012 Springer-Verlag.},
author = {Guet, Calin C and Gupta, Ashutosh and Henzinger, Thomas A and Mateescu, Maria and Sezgin, Ali},
location = {Berkeley, CA, USA},
pages = {294 -- 309},
publisher = {Springer},
title = {{Delayed continuous time Markov chains for genetic regulatory circuits}},
doi = {10.1007/978-3-642-31424-7_24},
volume = {7358 },
year = {2012},
}