human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "logical metric and algorithmic characterisations of probabilistic bisimulation"):
  Abstract: Many behavioural equivalences or preorders for probabilistic processes involve a lifting operation that turns a relation on states into a relation on distributions of states. We show that several existing proposals for lifting relations can be reconciled to be different presentations of essentially the same lifting operation. More interestingly, this lifting operation nicely corresponds to the Kantorovich metric, a fundamental concept used in mathematics to lift a metric on states to a metric on distributions of states, besides the fact the lifting operation is related to the maximum flow problem in optimisation theory. The lifting operation yields a neat notion of probabilistic bisimulation, for which we provide logical, metric, and algorithmic characterisations. Specifically, we extend the Hennessy-Milner logic and the modal mu-calculus with a new modality, resulting in an adequate and an expressive logic for probabilistic bisimilarity, respectively. The correspondence of the lifting operation and the Kantorovich metric leads to a natural characterisation of bisimulations as pseudometrics which are post-fixed points of a monotone function. We also present an “on the fly” algorithm to check if two states in a finitary system are related by probabilistic bisimilarity, exploiting the close relationship between the lifting operation and the maximum flow problem.

Includes members:
  Member "metrics for finite markov decision processes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "plannable approximations to mdp homomorphisms equivariance under actions")
  Member "metrics for markov decision processes with infinite state spaces":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning to control in metric space with optimal regret")
  Member "characterising probabilistic processes logically":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "logical characterization of bisimulation metrics")
  Member "approximating a behavioural pseudometric without discount for probabilistic systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "computing probabilistic bisimilarity distances for probabilistic automata")
  Member "characterising testing preorders for finite probabilistic processes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "ensuring liveness properties of distributed systems open problems")
  Member "flow faster efficient decision algorithms for probabilistic simulations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "bisimulations and logical characterizations on continuous time markov decision processes")

Question: Please tell me which class the source paper 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)