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: "control design along trajectories with sums of squares programming"
  Abstract: Motivated by the need for formal guarantees on the stability and safety of controllers for challenging robot control tasks, we present a control design procedure that explicitly seeks to maximize the size of an invariant "funnel" that leads to a predefined goal set. Our certificates of invariance are given in terms of sums of squares proofs of a set of appropriately defined Lyapunov inequalities. These certificates, together with our proposed polynomial controllers, can be efficiently obtained via semidefinite optimization. Our approach can handle time-varying dynamics resulting from tracking a given trajectory, input saturations (e.g. torque limits), and can be extended to deal with uncertainty in the dynamics and state. The resulting controllers can be used by space-filling feedback motion planning algorithms to fill up the space with significantly fewer trajectories. We demonstrate our approach on a severely torque limited underactuated double pendulum (Acrobot) and provide extensive simulation and hardware validation.

Connected through hyperedge HE-1 (induced by source paper "local policy optimization for trajectory centric reinforcement learning"):
  with members:
    - "benchmarking model based reinforcement learning"
    - "neural network dynamics for model based deep reinforcement learning with model free fine tuning"
    - "guided policy search as approximate mirror descent"
    - "path integral guided policy search"
    - "end to end training of deep visuomotor policies"

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"
    - "learning lyapunov potential functions from counterexamples and demonstrations"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "learning dynamic polynomial proofs"):
  with members:
    - "holist an environment for machine learning of higher order theorem proving"
    - "learning a sat solver from single bit supervision"
    - "machine learning for combinatorial optimization a methodological tour d horizon"
    - "gamepad a learning environment for theorem proving"
    - "reinforcement learning of theorem proving"
    - "sum of squares proofs and the quest toward optimal algorithms"
    - "playing atari with deep reinforcement learning"

Connected through hyperedge HE-4 (induced by source paper "teleoperator imitation with continuous time safety"):
  with members:
    - "learning contracting vector fields for stable imitation learning"
    - "real time perception meets reactive motion generation"
    - "deep imitation learning for complex manipulation tasks from virtual reality teleoperation"

Connected through hyperedge HE-5 (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"
    - "learning lyapunov potential functions from counterexamples and demonstrations"
    - "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"

Connected through hyperedge HE-6 (induced by source paper "robust tracking with model mismatch for fast and safe planning an sos optimization approach"):
  with members:
    - "fastrack a modular framework for fast and guaranteed safe motion planning"
    - "safe trajectory synthesis for autonomous driving in unforeseen environments"
    - "evaluating trajectory collision probability through adaptive importance sampling for safe motion planning"
    - "funnel libraries for real time robust feedback motion planning"
    - "optimal sampling based motion planning under differential constraints the drift case with linear affine dynamics"
    - "asymptotically optimal sampling based kinodynamic planning"
    - "optimal sampling based motion planning under differential constraints the driftless case"
    - "sampling based algorithms for optimal motion planning"

Connected through hyperedge HE-7 (induced by source paper "finite horizon backward reachability analysis and control synthesis for uncertain nonlinear systems"):
  with members:
    - "reachability analysis using dissipation inequalities for nonlinear dynamical systems"
    - "funnel libraries for real time robust feedback motion planning"

Connected through hyperedge HE-8 (induced by source paper "path following through control funnel functions"):
  with members:
    - "learning control lyapunov functions from counterexamples and demonstrations"
    - "learning lyapunov potential functions from counterexamples and demonstrations"

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.RO(Robotics)