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: "finite optimal control for time bounded reachability in ctmdps and continuous time markov games"
  Abstract: We establish the existence of optimal scheduling strategies for time-bounded reachability in continuous-time Markov decision processes, and of co-optimal strategies for continuous-time Markov games. Furthermore, we show that optimal control does not only exist, but has a surprisingly simple structure: The optimal schedulers from our proofs are deterministic and timed-positional, and the bounded time can be divided into a finite number of intervals, in which the optimal strategies are positional. That is, we demonstrate the existence of finite optimal control. Finally, we show that these pleasant properties of Markov decision processes extend to the more general class of continuous-time Markov games, and that both early and late schedulers show this behaviour.

Connected through hyperedge HE-1 (induced by source paper "policy learning for time bounded reachability in continuous time markov decision processes via doubly stochastic gradient ascent"):
  with members:
    - "learning and designing stochastic processes from logical constraints"
    - "optimal continuous time markov decisions"
    - "smoothed model checking for uncertain continuous time markov chains"
    - "path integral policy improvement with covariance matrix adaptation"
    - "experiments with infinite horizon policy gradient estimation"

Connected through hyperedge HE-2 (induced by source paper "bisimulations and logical characterizations on continuous time markov decision processes"):
  with members:
    - "bisimulations meet pctl equivalences for probabilistic automata"
    - "computing distances between probabilistic automata"
    - "efficient approximation of optimal control for markov games"
    - "flow faster efficient decision algorithms for probabilistic simulations"

Connected through hyperedge HE-3 (induced by source paper "transient reward approximation for continuous time markov chains"):
  with members:
    - "fluid model checking"
    - "optimal time abstract schedulers for ctmdps and markov games"

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.FL(Formal Languages and Automata Theory)