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 "faster statistical model checking for unbounded temporal properties"):
  Abstract: We present a new algorithm for the statistical model checking of Markov chains with respect to unbounded temporal properties, such as reachability and full linear temporal logic. The main idea is that we monitor each simulation run on the fly, in order to detect quickly if a bottom strongly connected component is entered with high probability, in which case the simulation run can be terminated early. As a result, our simulation runs are often much shorter than required by termination bounds that are computed a priori for a desired level of confidence and size of the state space. In comparison to previous algorithms for statistical model checking, for a given level of confidence, our method is not only faster in many cases but also requires less information about the system, namely, only the minimum transition probability that occurs in the Markov chain, thus enabling almost complete black-box verification. In addition, our method can be generalised to unbounded quantitative properties such as mean-payoff bounds.

Includes members:
  Member "verification of markov decision processes using learning algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "tractable reinforcement learning of signal temporal logic objectives")
  Member "uppaal smc statistical model checking for priced timed automata":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "quantitative aspects of programming languages and systems over the past 2 4 years and beyond")
  Member "robustness of structurally equivalent concurrent parity games":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "proving expected sensitivity of probabilistic programs with randomized variable dependent termination time")

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)