scholarly journals A Pattern Logic for Automata with Outputs

2020 ◽  
Vol 31 (06) ◽  
pp. 711-748
Author(s):  
Emmanuel Filiot ◽  
Nicolas Mazzocchi ◽  
Jean-François Raskin
Keyword(s):  
Model Checking ◽  
Structural Properties ◽  
Polynomial Time ◽  
Finite Automata ◽  
Structural Patterns ◽  
Complexity Results

We introduce a logic to express structural properties of automata with string inputs and, possibly, outputs in some monoid. In this logic, the set of predicates talking about the output values is parametric. We then consider three particular automata models (finite automata, transducers and automata weighted by integers here called sum-automata) and instantiate the generic logic for each of them. We give tight complexity results for the three logics with respect to the model-checking problem, depending on whether the formula is fixed or not. We study the expressiveness of our logics by expressing classical structural patterns characterising for instance finite ambiguity and polynomial ambiguity in the case of finite automata, determinisability and finite-valuedness in the case of transducers and sum-automata. As a consequence of our complexity results, we directly obtain that these classical properties can be decided in polynomial time.

High-accuracy prediction of protein structural classes using PseAA structural properties and secondary structural patterns

Biochimie ◽  
2014 ◽  
Vol 101 ◽  
pp. 104-112 ◽  
Author(s):  
Junru Wang ◽  
Yan Li ◽  
Xiaoqing Liu ◽  
Qi Dai ◽  
Yuhua Yao ◽  
...  
Keyword(s):  
Structural Properties ◽  
High Accuracy ◽  
Structural Patterns ◽  
Structural Classes

ORDINAL AUTOMATA AND CANTOR NORMAL FORM

2012 ◽  
Vol 23 (01) ◽  
pp. 87-98
Author(s):  
ZOLTÁN ÉSIK
Keyword(s):  
Normal Form ◽  
Polynomial Time ◽  
Regular Language ◽  
Finite Automata ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Order Type ◽  
Deterministic Finite Automaton ◽  
Lexicographic Ordering ◽  
Language L

It is known that an ordinal is the order type of the lexicographic ordering of a regular language if and only if it is less than ωω. We design a polynomial time algorithm that constructs, for each well-ordered regular language L with respect to the lexicographic ordering, given by a deterministic finite automaton, the Cantor Normal Form of its order type. It follows that there is a polynomial time algorithm to decide whether two deterministic finite automata accepting well-ordered regular languages accept isomorphic languages. We also give estimates on the state complexity of the smallest "ordinal automaton" representing an ordinal less than ωω, together with an algorithm that translates each such ordinal to an automaton.

Weak cardinality theorems

2005 ◽  
Vol 70 (3) ◽  
pp. 861-878
Author(s):  
Till Tantau
Keyword(s):  
Turing Machine ◽  
Polynomial Time ◽  
Computational Models ◽  
Finite Automata ◽  
Good Reason ◽  
Recursion Theory ◽  
Middle Ground ◽  
Logical Structures

AbstractKummer's Cardinality Theorem states that a language A must be recursive if a Turing machine can exclude for any n words , …, one of the n + 1 possibilities for the cardinality of {, …, }⋂ A. There was good reason to believe that this theorem is a peculiarity of recursion theory: neither the Cardinality Theorem nor weak forms of it hold for resource-bounded computational models like polynomial time. This belief may be flawed. In this paper it is shown that weak cardinality theorems hold for finite automata and also for other models. An explanation is proposed as to why recursion-theoretic and automata-theoretic weak cardinality theorems hold, but not corresponding 'middle-ground theorems': The recursion- and automata-theoretic weak cardinality theorems are instantiations of purely logical weak cardinality theorems. The logical theorems can be instantiated for logical structures characterizing recursive computations and finite automata computations. A corresponding structure characterizing polynomial time computations does not exist.

scholarly journals On Computational Tractability for Rational Verification

2019 ◽  
Author(s):  
Julian Gutierrez ◽  
Muhammad Najib ◽  
Giuseppe Perelli ◽  
Michael Wooldridge
Keyword(s):  
Model Checking ◽  
Temporal Logic ◽  
Multiagent Systems ◽  
Polynomial Time ◽  
Multiagent System ◽  
Reactive Systems ◽  
State System ◽  
Polynomial Space ◽  
Game Theoretic ◽  
Mean Payoff

Rational verification involves checking which temporal logic properties hold of a concurrent and multiagent system, under the assumption that agents in the system choose strategies in game theoretic equilibrium. Rational verification can be understood as a counterpart of model checking for multiagent systems, but while model checking can be done in polynomial time for some temporal logic specification languages such as CTL, and polynomial space with LTL specifications, rational verification is much more intractable: it is 2EXPTIME-complete with LTL specifications, even when using explicit-state system representations.  In this paper we show that the complexity of rational verification can be greatly reduced by restricting specifications to GR(1), a fragment of LTL that can represent most response properties of reactive systems. We also provide improved complexity results for rational verification when considering players' goals given by mean-payoff utility functions -- arguably the most widely used quantitative objective for agents in concurrent and multiagent systems. In particular, we show that for a number of relevant settings, rational verification can be done in polynomial space or even in polynomial time.

scholarly journals From Timed Automata to Logic - and Back

1995 ◽  
Vol 2 (2) ◽  
Author(s):  
Francois Laroussinie ◽  
Kim G. Larsen ◽  
Carsten Weise
Keyword(s):  
Model Checking ◽  
Real Time ◽  
Timed Automata ◽  
Finite Automata ◽  
Automatic Verification ◽  
Satisfiability Problem ◽  
Timed Automaton

One of the most successful techniques for automatic verification is that<br />of model checking. For finite automata there exist since long extremely<br />efficient model-checking algorithms, and in the last few years these algorithms have been made applicable to the verification of real-time automata using the region-techniques of Alur and Dill.<br />In this paper, we continue this transfer of existing techniques from the<br />setting of finite (untimed) automata to that of timed automata. In particular, a timed logic L is put forward, which is sufficiently expressive that we for any timed automaton may construct a single characteristic L formula uniquely characterizing the automaton up to timed bisimilarity. Also, we prove decidability of the satisfiability problem for L with respect to given bounds on the number of clocks and constants of the timed automata to be constructed. None of these results have as yet been succesfully accounted for in the presence of time.

scholarly journals Solving Vertex Cover in Polynomial Time on Hyperbolic Random Graphs

2021 ◽  
Author(s):  
Thomas Bläsius ◽  
Philipp Fischbeck ◽  
Tobias Friedrich ◽  
Maximilian Katzmann
Keyword(s):  
Computational Complexity ◽  
Structural Properties ◽  
Random Graphs ◽  
Polynomial Time ◽  
Real World ◽  
Degree Distribution ◽  
High Probability ◽  
Vertex Cover ◽  
Optimal Solution ◽  
Np Complete

AbstractThe computational complexity of the VertexCover problem has been studied extensively. Most notably, it is NP-complete to find an optimal solution and typically NP-hard to find an approximation with reasonable factors. In contrast, recent experiments suggest that on many real-world networks the run time to solve VertexCover is way smaller than even the best known FPT-approaches can explain. We link these observations to two properties that are observed in many real-world networks, namely a heterogeneous degree distribution and high clustering. To formalize these properties and explain the observed behavior, we analyze how a branch-and-reduce algorithm performs on hyperbolic random graphs, which have become increasingly popular for modeling real-world networks. In fact, we are able to show that the VertexCover problem on hyperbolic random graphs can be solved in polynomial time, with high probability. The proof relies on interesting structural properties of hyperbolic random graphs. Since these predictions of the model are interesting in their own right, we conducted experiments on real-world networks showing that these properties are also observed in practice.

Optimal Screening of Populations with Heterogeneous Risk Profiles Under the Availability of Multiple Tests

2021 ◽  
Author(s):  
Hrayer Aprahamian ◽  
Hadi El-Amine
Keyword(s):  
Objective Function ◽  
Structural Properties ◽  
Polynomial Time ◽  
Network Flow ◽  
Optimization Problem ◽  
Flow Problem ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Network Flow Problem ◽  
Multiple Tests

We study the design of large-scale group testing schemes under a heterogeneous population (i.e., subjects with potentially different risk) and with the availability of multiple tests. The objective is to classify the population as positive or negative for a given binary characteristic (e.g., the presence of an infectious disease) as efficiently and accurately as possible. Our approach examines components often neglected in the literature, such as the dependence of testing cost on the group size and the possibility of no testing, which are especially relevant within a heterogeneous setting. By developing key structural properties of the resulting optimization problem, we are able to reduce it to a network flow problem under a specific, yet not too restrictive, objective function. We then provide results that facilitate the construction of the resulting graph and finally provide a polynomial time algorithm. Our case study, on the screening of HIV in the United States, demonstrates the substantial benefits of the proposed approach over conventional screening methods. Summary of Contribution: This paper studies the problem of testing heterogeneous populations in groups in order to reduce costs and hence allow for the use of more efficient tests for high-risk groups. The resulting problem is a difficult combinatorial optimization problem that is NP-complete under a general objective. Using structural properties specific to our objective function, we show that the problem can be cast as a network flow problem and provide a polynomial time algorithm.

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