human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "decisive markov chains"
  Abstract: We consider qualitative and quantitative verification problems for infinite- state Markov chains. We call a Markov chain decisive w.r.t. a given set of target states F if it almost certainly eventually reaches either F or a state from which F can no longer be reached. While all finite Markov chains are trivially decisive (for every set F), this also holds for many classes of infinite Markov chains. Infinite Markov chains which contain a finite attractor are decisive w.r.t. every set F. In particular, all Markov chains induced by probabilistic lossy channel systems (PLCS) con- tain a finite attractor and are thus decisive. Furthermore, all globally coarse Markov chains are decisive. The class of globally coarse Markov chains includes, e.g., those induced by probabilistic vector addition systems (PVASS) with upward-closed sets F, and all Markov chains induced by probabilistic noisy Turing machines (PNTM) (a generalization of the noisy Turing machines (NTM) of Asarin and Collins). We consider both safety and liveness problems for decisive Markov chains. Safety: What is the probability that a given set of states F is eventually reached. Liveness: What is the probability that a given set of states is reached infinitely often. There are three variants of these questions. (1) The qualitative problem, i.e., deciding if the probability is one (or zero); (2) the approximate quantitative problem, i.e., computing the probability up-to arbitrary precision; (3) the exact quantitative problem, i.e., computing probabilities exactly. 1. We express the qualitative problem in abstract terms for decisive Markov chains, and show an almost complete picture of its decidability for PLCS, PVASS and PNTM. 2. We also show that the path enumeration algorithm of Iyer and Narasimha terminates for decisive Markov chains and can thus be used to solve the approximate quantitative safety problem. A modified variant of this algorithm can be used to solve the approximate quantitative liveness problem. 3. Finally, we show that the exact probability of (repeatedly) reaching F cannot be effectively expressed (in a uniform way) in Tarski-algebra for either PLCS, PVASS or (P)NTM (unlike for probabilistic pushdown automata).

Connected through hyperedge HE-1 (induced by source paper "decisiveness of stochastic systems and its application to hybrid models"):
  with members:
    - "when are stochastic transition systems tameable"
    - "stochastic timed automata"
    - "statistical model checking for stochastic hybrid systems"

Connected through hyperedge HE-2 (induced by source paper "life is random time is not markov decision processes with window objectives"):
  with members:
    - "multi weighted markov decision processes with reachability objectives"
    - "expected window mean payoff"
    - "universal trees grow inside separating automata quasi polynomial lower bounds for parity games"
    - "the complexity of mean payoff games using universal graphs"
    - "extending finite memory determinacy by boolean combination of winning conditions"
    - "value iteration for long run average reward in markov decision processes"
    - "threshold constraints with guarantees for parity objectives in markov decision processes"
    - "a storm is coming a modern probabilistic model checker"

Connected through hyperedge HE-3 (induced by source paper "optimal satisfiability checking for arithmetic mu calculi"):
  with members:
    - "permutation games for the weakly aconjunctive mu calculus"
    - "satisfiability games for branching time logics"
    - "unifying buchi complementation constructions"
    - "exptime tableaux for the coalgebraic mu calculus"
    - "strong completeness of coalgebraic modal logics"
    - "pspace bounds for rank 1 modal logics"

Connected through hyperedge HE-4 (induced by source paper "maximizing the conditional expected reward for reaching the goal"):
  with members:
    - "termination analysis of probabilistic programs through positivstellensatz s"
    - "synthesizing probabilistic invariants via doob s decomposition"
    - "variations on the stochastic shortest path problem"
    - "the odds of staying on budget"
    - "markov decision processes with multiple long run averageobjectives"
    - "quantitative analysis of information leakage in probabilistic and nondeterministic systems"

Connected through hyperedge HE-5 (induced by source paper "when are stochastic transition systems tameable"):
  with members:
    - "stochastic timed automata"
    - "fixed delay events in generalized semi markov processes revisited"

Connected through hyperedge HE-6 (induced by source paper "an efficient synthesis algorithm for parametric markov chains against linear time properties"):
  with members:
    - "from ltl to deterministic automata a safraless compositional approach"
    - "automata with generalized rabin pairs for probabilistic model checking and ltl synthesis"

Connected through hyperedge HE-7 (induced by source paper "qualitative analysis of vass induced mdps"):
  with members:
    - "long run average behaviour of probabilistic vector addition systems"
    - "solving parity games on integer vectors"
    - "one counter stochastic games"
    - "one counter markov decision processes"
    - "qualitative logics and equivalences for probabilistic systems"

Connected through hyperedge HE-8 (induced by source paper "stochastic parity games on lossy channel systems"):
  with members:
    - "solving stochastic b uchi games on infinite arenas with a finite attractor"
    - "recursive concurrent stochastic games"
    - "verifying nondeterministic probabilistic channel systems against ω regular linear time properties"
    - "the existential theory of equations with rational constraints in free groups is pspace complete"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.LO(Logic in Computer Science)