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: "ergodic exploration of distributed information"
  Abstract: This paper presents an active search trajectory synthesis technique for autonomous mobile robots with nonlinear measurements and dynamics. The presented approach uses the ergodicity of a planned trajectory with respect to an expected information density map to close the loop during search. The ergodic control algorithm does not rely on discretization of the search or action spaces and is well posed for coverage with respect to the expected information density whether the information is diffuse or localized, thus trading off between exploration and exploitation in a single-objective function. As a demonstration, we use a robotic electrolocation platform to estimate location and size parameters describing static targets in an underwater environment. Our results demonstrate that the ergodic exploration of distributed information algorithm outperforms commonly used information-oriented controllers, particularly when distractions are present.

Connected through hyperedge HE-1 (induced by source paper "active area coverage from equilibrium"):
  with members:
    - "simple random search provides a competitive approach to reinforcement learning"
    - "decentralized ergodic control distribution driven sensing and exploration for multiagent systems"
    - "ergodic coverage in constrained environments using stochastic trajectory optimization"
    - "neural network dynamics for model based deep reinforcement learning with model free fine tuning"

Connected through hyperedge HE-2 (induced by source paper "task based hybrid shared control for training through forceful interaction"):
  with members:
    - "iterative sequential action control for stable model based control of nonlinear systems"
    - "sequential action control closed form optimal control for nonlinear and nonsmooth systems"
    - "algorithm for optimal mode scheduling in switched systems"

Connected through hyperedge HE-3 (induced by source paper "model based active source identification in complex environments"):
  with members:
    - "distributed state estimation using intermittently connected robot networks"
    - "multi robot informative path planning for active sensing of environmental phenomena a tale of two algorithms"

Connected through hyperedge HE-4 (induced by source paper "a successive elimination approach to adaptive robotic source seeking"):
  with members:
    - "model based active source identification in complex environments"
    - "multi armed bandits with metric movement costs"
    - "best of k bandits"
    - "bayesopt a bayesian optimization library for nonlinear optimization experimental design and bandits"
    - "information acquisition with sensing robots algorithms and error bounds"
    - "information theoretic regret bounds for gaussian process optimization in the bandit setting"

Connected through hyperedge HE-5 (induced by source paper "using neural networks to generate information maps for mobile sensors"):
  with members:
    - "efficient and low cost localization of radio signals with a multirotor uav"
    - "ergodic coverage in constrained environments using stochastic trajectory optimization"
    - "real time area coverage and target localization using receding horizon ergodic exploration"
    - "convolutional neural networks at constrained time cost"

Connected through hyperedge HE-6 (induced by source paper "decentralized ergodic control distribution driven sensing and exploration for multiagent systems"):
  with members:
    - "distributed active state estimation with user specified accuracy"
    - "real time area coverage and target localization using receding horizon ergodic exploration"
    - "ergodic exploration using binary sensing for nonparametric shape estimation"
    - "sequential action control closed form optimal control for nonlinear and nonsmooth systems"

Connected through hyperedge HE-7 (induced by source paper "data driven measurement models for active localization in sparse environments"):
  with members:
    - "real time area coverage and target localization using receding horizon ergodic exploration"
    - "ergodic exploration using binary sensing for nonparametric shape estimation"
    - "synthesizing training data for object detection in indoor scenes"

Connected through hyperedge HE-8 (induced by source paper "learning models for shared control of human machine systems with unknown dynamics"):
  with members:
    - "model based control using koopman operators"
    - "shared autonomy via hindsight optimization"

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)