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: "reachability in augmented interval markov chains"
  Abstract: In this paper we propose augmented interval Markov chains (AIMCs): a generalisation of the familiar interval Markov chains (IMCs) where uncertain transition probabilities are in addition allowed to depend on one another. This new model preserves the flexibility afforded by IMCs for describing stochastic systems where the parameters are unclear, for example due to measurement error, but also allows us to specify transitions with probabilities known to be identical, thereby lending further expressivity. #R##N#The focus of this paper is reachability in AIMCs. We study the qualitative, exact quantitative and approximate reachability problem, as well as natural subproblems thereof, and establish several upper and lower bounds for their complexity. We prove the exact reachability problem is at least as hard as the famous square-root sum problem, but, encouragingly, the approximate version lies in $\mathbf{NP}$ if the underlying graph is known, whilst the restriction of the exact problem to a constant number of uncertain edges is in $\mathbf{P}$. Finally, we show that uncertainty in the graph structure affects complexity by proving $\mathbf{NP}$-completeness for the qualitative subproblem, in contrast with an easily-obtained upper bound of $\mathbf{P}$ for the same subproblem with known graph structure.

Connected through hyperedge HE-1 (induced by source paper "parameter synthesis for markov models"):
  with members:
    - "shepherding hordes of markov chains"
    - "parameter independent strategies for pmdps via pomdps"
    - "sea param exploring schedulers in parametric mdps"
    - "multi objective robust strategy synthesis for interval markov decision processes"
    - "parametric markov chains pctl complexity and fraction free gaussian elimination"
    - "sequential convex programming for the efficient verification of parametric mdps"
    - "a storm is coming a modern probabilistic model checker"
    - "parameter synthesis for markov models faster than ever"

Connected through hyperedge HE-2 (induced by source paper "are parametric markov chains monotonic"):
  with members:
    - "on the complexity of reachability in parametric markov decision processes"
    - "accelerated model checking of parametric markov chains"
    - "parametric markov chains pctl complexity and fraction free gaussian elimination"
    - "a storm is coming a modern probabilistic model checker"
    - "the complexity of graph based reductions for reachability in markov decision processes"
    - "parameter synthesis for markov models faster than ever"
    - "accelerating parametric probabilistic verification"

Connected through hyperedge HE-3 (induced by source paper "shepherding hordes of markov chains"):
  with members:
    - "parameter independent strategies for pmdps via pomdps"
    - "a storm is coming a modern probabilistic model checker"
    - "a symbolic sat based algorithm for almost sure reachability with small strategies in pomdps"
    - "optimal cost almost sure reachability in pomdps"

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.CC(Computational Complexity)