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: "online uav path planning for joint detection and tracking of multiple radio tagged objects"
  Abstract: We consider the problem of online path planning for joint detection and tracking of multiple unknown radio-tagged objects. This is a necessary task for gathering spatio-temporal information using UAVs with on-board sensors in a range of monitoring applications. In this paper, we propose an online path planning algorithm with joint detection and tracking for the problem because signal measurements from these object are inherently noisy. We derive a partially observable Markov decision process with a random finite set track-before-detect (TBD) multi-object filter. We show that, in practice, the likelihood function of raw signals received by the UAV transformed into the time-frequency domain is separable for multiple radio-tagged objects and results in a numerically efficient multi-object TBD filter. We derive a TBD filter with a jump Markov system to accommodate maneuvering objects capable of switching between different dynamic modes. Further, we impose a practical constraint using a void probability formulation to maintain a safe distance between the UAV and objects of interest. Our evaluations demonstrate the capability of our approach handle multiple radio-tagged object behaviors such as birth, death, motion modes and the superiority of the proposed online planning method with the TBD-based filter at tracking and detecting objects compared to the detection-based counterpart, especially under low signal-to-noise ratio environments.

Connected through hyperedge HE-1 (induced by source paper "multi objective multi agent planning for jointly discovering and tracking mobile object"):
  with members:
    - "trackerbots autonomous unmanned aerial vehicle for real time localization and tracking of multiple radio tagged animals"
    - "trackerbots autonomous unmanned aerial vehicle for real time localization and tracking of multiple radio tagged animals"
    - "sensor management for multi target tracking via multi bernoulli filtering"

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)