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 "a complete quantitative deduction system for the bisimilarity distance on markov chains"):
  Abstract: In this paper we propose a complete axiomatization of the bisimilarity#N#distance of Desharnais et al. for the class of finite labelled Markov chains.#N#Our axiomatization is given in the style of a quantitative extension of#N#equational logic recently proposed by Mardare, Panangaden, and Plotkin (LICS#N#2016) that uses equality relations $t \equiv_\varepsilon s$ indexed by#N#rationals, expressing that `$t$ is approximately equal to $s$ up to an error#N#$\varepsilon$'. Notably, our quantitative deduction system extends in a natural#N#way the equational system for probabilistic bisimilarity given by Stark and#N#Smolka by introducing an axiom for dealing with the Kantorovich distance#N#between probability distributions. The axiomatization is then used to propose a#N#metric extension of a Kleene's style representation theorem for finite labelled#N#Markov chains, that was proposed (in a more general coalgebraic fashion) by#N#Silva et al. (Inf. Comput. 2011).

Includes members:
  Member "mixed powerdomains for probability and nondeterminism":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the ideal approach to computing closed subsets in well quasi orderings")
  Member "sound and complete axiomatizations of coalgebraic language equivalence":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "toward a uniform theory of effectful state machines")
  Member "approximating a behavioural pseudometric without discount for probabilistic systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "computing probabilistic bisimilarity distances for probabilistic automata")

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)