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: "qualitative logics and equivalences for probabilistic systems"
  Abstract: We investigate logics and equivalence relations that capture the qualitative#N#behavior of Markov Decision Processes (MDPs). We present Qualitative Randomized#N#CTL (QRCTL): formulas of this logic can express the fact that certain temporal#N#properties hold over all paths, or with probability 0 or 1, but they do not#N#distinguish among intermediate probability values. We present a symbolic,#N#polynomial time model-checking algorithm for QRCTL on MDPs.#N#  The logic QRCTL induces an equivalence relation over states of an MDP that we#N#call qualitative equivalence: informally, two states are qualitatively#N#equivalent if the sets of formulas that hold with probability 0 or 1 at the two#N#states are the same. We show that for finite alternating MDPs, where#N#nondeterministic and probabilistic choices occur in different states,#N#qualitative equivalence coincides with alternating bisimulation, and can thus#N#be computed via efficient partition-refinement algorithms. On the other hand,#N#in non-alternating MDPs the equivalence relations cannot be computed via#N#partition-refinement algorithms, but rather, they require non-local#N#computation. Finally, we consider QRCTL*, that extends QRCTL with nested#N#temporal operators in the same manner in which CTL* extends CTL. We show that#N#QRCTL and QRCTL* induce the same qualitative equivalence on alternating MDPs,#N#while on non-alternating MDPs, the equivalence arising from QRCTL* can be#N#strictly finer. We also provide a full characterization of the relation between#N#qualitative equivalence, bisimulation, and alternating bisimulation, according#N#to whether the MDPs are finite, and to whether their transition relations are#N#finitely-branching.

Connected through hyperedge HE-1 (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"
    - "decisive markov chains"

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)