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: "characterising probabilistic processes logically"
  Abstract: In this paper we work on (bi)simulation semantics of processes that exhibit both nondeterministic and probabilistic behaviour. We propose a probabilistic extension of the modal mu-calculus and show how to derive characteristic formulae for various simulation-like preorders over finite-state processes without divergence. In addition, we show that even without the fixpoint operators this probabilistic mu-calculus can be used to characterise these behavioural relations in the sense that two states are equivalent if and only if they satisfy the same set of formulae.

Connected through hyperedge HE-1 (induced by source paper "logical characterization of bisimulation metrics"):
  with members:
    - "divide and congruence ii from decomposition of modal formulas to preservation of delay and weak bisimilarity"
    - "modal characterisations of behavioural pseudometrics"
    - "topologies of stochastic markov models computational aspects"
    - "probabilistic bisimulation naturally on distributions"
    - "fixed point characterization of compositionality properties of probabilistic processes combinators"
    - "when equivalence and bisimulation join forces in probabilistic automata"
    - "continuous markovian logics axiomatization and quantified metatheory"
    - "logical metric and algorithmic characterisations of probabilistic bisimulation"

Connected through hyperedge HE-2 (induced by source paper "łukasiewicz mu calculus"):
  with members:
    - "probabilistic modal mu calculus with independent product"
    - "on the equivalence of game and denotational semantics for the probabilistic mu calculus"

Connected through hyperedge HE-3 (induced by source paper "bisimulations meet pctl equivalences for probabilistic automata"):
  with members:
    - "computing distances between probabilistic automata"

Connected through hyperedge HE-4 (induced by source paper "logical metric and algorithmic characterisations of probabilistic bisimulation"):
  with members:
    - "metrics for finite markov decision processes"
    - "metrics for markov decision processes with infinite state spaces"
    - "approximating a behavioural pseudometric without discount for probabilistic systems"
    - "characterising testing preorders for finite probabilistic processes"
    - "flow faster efficient decision algorithms for probabilistic simulations"

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)