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: "learning lyapunov potential functions from counterexamples and demonstrations"
  Abstract: We present a technique for learning control Lyapunov (potential) functions, which are used in turn to synthesize controllers for nonlinear dynamical systems. The learning framework uses a demonstrator that implements a black-box, untrusted strategy presumed to solve the problem of interest, a learner that poses finitely many queries to the demonstrator to infer a candidate function and a verifier that checks whether the current candidate is a valid control Lyapunov function. The overall learning framework is iterative, eliminating a set of candidates on each iteration using the counterexamples discovered by the verifier and the demonstrations over these counterexamples. We prove its convergence using ellipsoidal approximation techniques from convex optimization. We also implement this scheme using nonlinear MPC controllers to serve as demonstrators for a set of state and trajectory stabilization problems for nonlinear dynamical systems. Our approach is able to synthesize relatively simple polynomial control Lyapunov functions, and in that process replace the MPC using a guaranteed and computationally less expensive controller.

Connected through hyperedge HE-1 (induced by source paper "episodic learning with control lyapunov functions for uncertain robotic systems"):
  with members:
    - "stable gaussian process based tracking control of euler lagrange systems"
    - "a control lyapunov perspective on episodic learning via projection to state stability"
    - "end to end safe reinforcement learning through barrier functions for safety critical continuous control tasks"
    - "neural lander stable drone landing control using learned dynamics"
    - "the lyapunov neural network adaptive stability certification for safe learning of dynamical systems"
    - "sim to real learning agile locomotion for quadruped robots"
    - "a lyapunov based approach to safe reinforcement learning"
    - "accelerating imitation learning with predictive models"

Connected through hyperedge HE-2 (induced by source paper "learning control lyapunov functions from counterexamples and demonstrations"):
  with members:
    - "path following through control funnel functions"
    - "safe learning of quadrotor dynamics using barrier certificates"
    - "a theory of formal synthesis via inductive learning"
    - "counterexample guided synthesis of switched controllers for reach while stay properties"
    - "controller synthesis with inductive proofs for piecewise linear systems an smt based algorithm"
    - "counter example guided synthesis of control lyapunov functions for switched systems"
    - "learning deep control policies for autonomous aerial vehicles with mpc guided policy search"
    - "torque saturation in bipedal robotic walking through control lyapunov function based quadratic programs"

Connected through hyperedge HE-3 (induced by source paper "inductive certificate synthesis for control design"):
  with members:
    - "learning control lyapunov functions from counterexamples and demonstrations"
    - "path following through control funnel functions"
    - "the reach avoid problem for constant rate multi mode systems"
    - "automated formal synthesis of digital controllers for state space physical plants"
    - "a theory of formal synthesis via inductive learning"
    - "counterexample guided synthesis of switched controllers for reach while stay properties"
    - "controller synthesis with inductive proofs for piecewise linear systems an smt based algorithm"
    - "counter example guided synthesis of control lyapunov functions for switched systems"

Connected through hyperedge HE-4 (induced by source paper "path following through control funnel functions"):
  with members:
    - "learning control lyapunov functions from counterexamples and demonstrations"
    - "control design along trajectories with sums of squares programming"

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.SY(Systems and Control)