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 "policy learning for time bounded reachability in continuous time markov decision processes via doubly stochastic gradient ascent"):
  Abstract: Continuous-time Markov decision processes are an important class of models in a wide range of applications, ranging from cyber-physical systems to synthetic biology. A central problem is how to devise a policy to control the system in order to maximise the probability of satisfying a set of temporal logic specifications. Here we present a novel approach based on statistical model checking and an unbiased estimation of a functional gradient in the space of possible policies. The statistical approach has several advantages over conventional approaches based on uniformisation, as it can also be applied when the model is replaced by a black box, and does not suffer from state-space explosion. The use of a stochastic gradient to guide our search considerably improves the efficiency of learning policies. We demonstrate the method on a proof-of-principle non-linear population model, showing strong performance in a non-trivial task.

Includes members:
  Member "learning and designing stochastic processes from logical constraints":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "characterization and complexity results on jumping finite automata")
  Member "optimal continuous time markov decisions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "continuous time markov decisions based on partial exploration")
  Member "smoothed model checking for uncertain continuous time markov chains":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "parameter synthesis for markov models")
  Member "path integral policy improvement with covariance matrix adaptation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the differentiable cross entropy method")
  Member "finite optimal control for time bounded reachability in ctmdps and continuous time markov games":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "bisimulations and logical characterizations on continuous time markov decision processes")
  Member "experiments with infinite horizon policy gradient estimation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal and low complexity dynamic spectrum access for rf powered ambient backscatter system with online reinforcement learning")

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.SY(Systems and Control)