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: "dynamic task execution using active parameter identification with the baxter research robot"
  Abstract: This paper presents experimental results from the real-time parameter estimation of a system model and subsequent trajectory optimization for a dynamic task using the Baxter Research Robot from Rethink Robotics. An active estimator maximizing Fisher information is used in real time with a closed-loop, nonlinear control technique known as sequential action control. Baxter is tasked with estimating the length of a string connected to a load suspended from the gripper with a load cell providing the single source of feedback to the estimator. Following the active estimation, a trajectory is generated using the  trep  software package that controls Baxter to dynamically swing a suspended load into a box. Several trials are presented with varying initial estimates showing that the estimation is required to obtain adequate open-loop trajectories to complete the prescribed task. The result of one trial with and without the active estimation is also shown in the accompanying video.

Connected through hyperedge HE-1 (induced by source paper "active learning of dynamics for data driven control using koopman operators"):
  with members:
    - "learning models for shared control of human machine systems with unknown dynamics"
    - "learning deep neural network representations for koopman operators of nonlinear dynamical systems"
    - "neural network dynamics for model based deep reinforcement learning with model free fine tuning"
    - "preparing for the unknown learning a universal policy with online system identification"
    - "model based control using koopman operators"
    - "pulse based control using koopman operator under parametric uncertainty"
    - "sequential action control closed form optimal control for nonlinear and nonsmooth systems"
    - "asynchronous methods for deep reinforcement learning"

Connected through hyperedge HE-2 (induced by source paper "real time area coverage and target localization using receding horizon ergodic exploration"):
  with members:
    - "communication free distributed coverage for networked systems"
    - "autonomous visual rendering using physical motion"
    - "iterative sequential action control for stable model based control of nonlinear systems"
    - "sequential action control closed form optimal control for nonlinear and nonsmooth systems"
    - "ergodic exploration of distributed information"
    - "multi robot informative path planning for active sensing of environmental phenomena a tale of two algorithms"
    - "persistent robotic tasks monitoring and sweeping in changing environments"
    - "efficient informative sensing using multiple robots"

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)