@article{1731,
abstract = {We consider two-player zero-sum games on graphs. These games can be classified on the basis of the information of the players and on the mode of interaction between them. On the basis of information the classification is as follows: (a) partial-observation (both players have partial view of the game); (b) one-sided complete-observation (one player has complete observation); and (c) complete-observation (both players have complete view of the game). On the basis of mode of interaction we have the following classification: (a) concurrent (both players interact simultaneously); and (b) turn-based (both players interact in turn). The two sources of randomness in these games are randomness in transition function and randomness in strategies. In general, randomized strategies are more powerful than deterministic strategies, and randomness in transitions gives more general classes of games. In this work we present a complete characterization for the classes of games where randomness is not helpful in: (a) the transition function probabilistic transition can be simulated by deterministic transition); and (b) strategies (pure strategies are as powerful as randomized strategies). As consequence of our characterization we obtain new undecidability results for these games. },
author = {Chatterjee, Krishnendu and Doyen, Laurent and Gimbert, Hugo and Henzinger, Thomas A},
journal = {Information and Computation},
number = {12},
pages = {3 -- 16},
publisher = {Elsevier},
title = {{Randomness for free}},
doi = {10.1016/j.ic.2015.06.003},
volume = {245},
year = {2015},
}
@article{1832,
abstract = {Linearizability of concurrent data structures is usually proved by monolithic simulation arguments relying on the identification of the so-called linearization points. Regrettably, such proofs, whether manual or automatic, are often complicated and scale poorly to advanced non-blocking concurrency patterns, such as helping and optimistic updates. In response, we propose a more modular way of checking linearizability of concurrent queue algorithms that does not involve identifying linearization points. We reduce the task of proving linearizability with respect to the queue specification to establishing four basic properties, each of which can be proved independently by simpler arguments. As a demonstration of our approach, we verify the Herlihy and Wing queue, an algorithm that is challenging to verify by a simulation proof. },
author = {Chakraborty, Soham and Henzinger, Thomas A and Sezgin, Ali and Vafeiadis, Viktor},
journal = {Logical Methods in Computer Science},
number = {1},
publisher = {International Federation of Computational Logic},
title = {{Aspect-oriented linearizability proofs}},
doi = {10.2168/LMCS-11(1:20)2015},
volume = {11},
year = {2015},
}
@inproceedings{1659,
abstract = {The target discounted-sum problem is the following: Given a rational discount factor 0 < λ < 1 and three rational values a, b, and t, does there exist a finite or an infinite sequence w ε(a, b)∗ or w ε(a, b)w, such that Σ|w| i=0 w(i)λi equals t? The problem turns out to relate to many fields of mathematics and computer science, and its decidability question is surprisingly hard to solve. We solve the finite version of the problem, and show the hardness of the infinite version, linking it to various areas and open problems in mathematics and computer science: β-expansions, discounted-sum automata, piecewise affine maps, and generalizations of the Cantor set. We provide some partial results to the infinite version, among which are solutions to its restriction to eventually-periodic sequences and to the cases that λ λ 1/2 or λ = 1/n, for every n ε N. We use our results for solving some open problems on discounted-sum automata, among which are the exact-value problem for nondeterministic automata over finite words and the universality and inclusion problems for functional automata.},
author = {Boker, Udi and Henzinger, Thomas A and Otop, Jan},
booktitle = {LICS},
issn = {1043-6871 },
location = {Kyoto, Japan},
pages = {750 -- 761},
publisher = {IEEE},
title = {{The target discounted-sum problem}},
doi = {10.1109/LICS.2015.74},
year = {2015},
}
@article{1840,
abstract = {In this paper, we present a method for reducing a regular, discrete-time Markov chain (DTMC) to another DTMC with a given, typically much smaller number of states. The cost of reduction is defined as the Kullback-Leibler divergence rate between a projection of the original process through a partition function and a DTMC on the correspondingly partitioned state space. Finding the reduced model with minimal cost is computationally expensive, as it requires an exhaustive search among all state space partitions, and an exact evaluation of the reduction cost for each candidate partition. Our approach deals with the latter problem by minimizing an upper bound on the reduction cost instead of minimizing the exact cost. The proposed upper bound is easy to compute and it is tight if the original chain is lumpable with respect to the partition. Then, we express the problem in the form of information bottleneck optimization, and propose using the agglomerative information bottleneck algorithm for searching a suboptimal partition greedily, rather than exhaustively. The theory is illustrated with examples and one application scenario in the context of modeling bio-molecular interactions.},
author = {Geiger, Bernhard and Petrov, Tatjana and Kubin, Gernot and Koeppl, Heinz},
issn = {0018-9286},
journal = {IEEE Transactions on Automatic Control},
number = {4},
pages = {1010 -- 1022},
publisher = {IEEE},
title = {{Optimal Kullback-Leibler aggregation via information bottleneck}},
doi = {10.1109/TAC.2014.2364971},
volume = {60},
year = {2015},
}
@article{1698,
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. Multi-mean-payoff and multi-energy games replace individual weights by tuples, and the limit average (resp., running sum) of each coordinate must be (resp., remain) nonnegative. We prove finite-memory determinacy of multi-energy games and show inter-reducibility of multi-mean-payoff and multi-energy games for finite-memory strategies. We improve the computational complexity for solving both classes with finite-memory strategies: we prove coNP-completeness improving the previous known EXPSPACE bound. For memoryless strategies, we show that deciding the existence of a winning strategy for the protagonist is NP-complete. We present the first solution of multi-mean-payoff games with infinite-memory strategies: we show that mean-payoff-sup objectives can be decided in NP∩coNP, whereas mean-payoff-inf objectives are coNP-complete.},
author = {Velner, Yaron and Chatterjee, Krishnendu and Doyen, Laurent and Henzinger, Thomas A and Rabinovich, Alexander and Raskin, Jean},
journal = {Information and Computation},
number = {4},
pages = {177 -- 196},
publisher = {Elsevier},
title = {{The complexity of multi-mean-payoff and multi-energy games}},
doi = {10.1016/j.ic.2015.03.001},
volume = {241},
year = {2015},
}