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 "formal policy learning from demonstrations for reachability properties"):
  Abstract: We consider the problem of learning structured, closed-loop policies (feedback laws) from demonstrations in order to control under-actuated robotic systems, so that formal behavioral specifications such as reaching a target set of states are satisfied. Our approach uses a ``counterexample-guided'' iterative loop that involves the interaction between a policy learner, a demonstrator and a verifier. The learner is responsible for querying the demonstrator in order to obtain the training data to guide the construction of a policy candidate. This candidate is analyzed by the verifier and either accepted as correct, or rejected with a counterexample. In the latter case, the counterexample is used to update the training data and further refine the policy. #R##N#The approach is instantiated using receding horizon model-predictive controllers (MPCs) as demonstrators. Rather than using regression to fit a policy to the demonstrator actions, we extend the MPC formulation with the gradient of the cost-to-go function evaluated at sample states in order to constrain the set of policies compatible with the behavior of the demonstrator. We demonstrate the successful application of the resulting policy learning schemes on two case studies and we show how simple, formally-verified policies can be inferred starting from a complex and unverified nonlinear MPC implementations. As a further benefit, the policies are many orders of magnitude faster to implement when compared to the original MPCs.

Includes members:
  Member "learning control lyapunov functions from counterexamples and demonstrations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep learning tubes for tube mpc")
  Member "sound and automated synthesis of digital stabilizing controllers for continuous plants":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "automated formal synthesis of digital controllers for state space physical plants")
  Member "plato policy learning using adaptive trajectory optimization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "adapt zero shot adaptive policy transfer for stochastic dynamical systems")
  Member "a theory of formal synthesis via inductive learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analyzing cyber physical systems from the perspective of artificial intelligence")
  Member "controller synthesis with inductive proofs for piecewise linear systems an smt based algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hyperproperties for robotics planning via hyperltl")
  Member "counter example guided synthesis of control lyapunov functions for switched systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning control lyapunov functions from counterexamples and demonstrations")
  Member "a reduction of imitation learning and structured prediction to no regret online learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "safe imitation learning via fast bayesian reward inference from preferences")
  Member "webotstm professional mobile robot simulation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "cinemairsim a camera realistic robotics simulator for cinematographic purposes")

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)