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 "prescribed performance control guided policy improvement for satisfying signal temporal logic tasks"):
  Abstract: Signal temporal logic (STL) provides a user-friendly interface for defining complex tasks for robotic systems. Recent efforts aim at designing control laws or using reinforcement learning methods to find policies which guarantee satisfaction of these tasks. While the former suffer from the trade-off between task specification and computational complexity, the latter encounter difficulties in exploration as the tasks become more complex and challenging to satisfy. This paper proposes to combine the benefits of the two approaches and use an efficient prescribed performance control (PPC) base law to guide exploration within the reinforcement learning algorithm. The potential of the method is demonstrated in a simulated environment through two sample navigational tasks.

Includes members:
  Member "a policy search method for temporal logic specified reinforcement learning tasks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "control synthesis from linear temporal logic specifications using model free reinforcement learning")
  Member "q learning for robust satisfaction of signal temporal logic specifications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "tractable reinforcement learning of signal temporal logic objectives")
  Member "robust control for signal temporal logic specifications using average space robustness":
    also connected through other hyperedges:
      (none)
  Member "path integral guided policy search":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "local policy optimization for trajectory centric reinforcement learning")
  Member "robust temporal logic model predictive control":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "continuous time signal temporal logic planning with control barrier function")
  Member "a learning based approach to control synthesis of markov decision processes for linear temporal logic specifications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "point based methods for model checking in partially observable markov decision processes")
  Member "path integral policy improvement with covariance matrix adaptation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the differentiable cross entropy method")

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)