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: "age optimal trajectory planning for uav assisted data collection"
  Abstract: Unmanned aerial vehicle (UAV)-aided data collection is a new and promising application in many practical scenarios. In this work, we study the age-optimal trajectory planning problem in UAV-enabled wireless sensor networks, where a UAV is dispatched to collect data from the ground sensor nodes (SNs). The age of information (AoI) collected from each SN is characterized by the data uploading time and the time elapsed since the UAV leaves this SN. We attempt to design two age-optimal trajectories, referred to as the Max-AoI-optimal and Ave-AoI-optimal trajectories, respectively. The Max-AoI-optimal trajectory planning is to minimize the age of the `oldest' sensed information among the SNs. The Ave-AoI-optimal trajectory planning is to minimize the average AoI of all the SNs. Then, we show that each age-optimal flight trajectory corresponds to a shortest Hamiltonian path in the wireless sensor network where the distance between any two SNs represents the amount of inter-visit time. The dynamic programming (DP) method and genetic algorithm (GA) are adopted to find the two different age-optimal trajectories. Simulation results validate the effectiveness of the proposed methods, and show how the UAV's trajectory is affected by the two AoI metrics.

Connected through hyperedge HE-1 (induced by source paper "deep reinforcement learning for fresh data collection in uav assisted iot networks"):
  with members:
    - "average peak age of information minimization in uav assisted iot networks"
    - "timely status update in massive iot systems decentralized scheduling for wireless uplinks"
    - "energy minimization for wireless communication with rotary wing uav"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "energy efficient uav communication with trajectory optimization"
    - "update or wait how to keep your data fresh"

Connected through hyperedge HE-2 (induced by source paper "average age of changed information in the internet of things"):
  with members:
    - "optimizing information freshness in computing enabled iot networks"
    - "the age of incorrect information a new performance metric for status updates"

Connected through hyperedge HE-3 (induced by source paper "3d trajectory optimization in rician fading for uav enabled data harvesting"):
  with members:
    - "capacity characterization of uav enabled two user broadcast channel"
    - "3 d placement of an unmanned aerial vehicle base station for maximum coverage of users with different qos requirements"
    - "optimal 3d trajectory design and resource allocation for solar powered uav communication systems"
    - "learning to communicate in uav aided wireless networks map based approaches"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"
    - "ultra reliable uav communication using altitude and cooperation diversity"
    - "trajectory design for distributed estimation in uav enabled wireless sensor network"
    - "uav enabled radio access network multi mode communication and trajectory design"

Connected through hyperedge HE-4 (induced by source paper "hybrid offline online design for uav enabled data harvesting in probabilistic los channel"):
  with members:
    - "average peak age of information minimization in uav assisted iot networks"
    - "efficient local map search algorithms for the placement of flying relays"
    - "interference management for cellular connected uavs a deep reinforcement learning approach"
    - "deep reinforcement learning for minimizing age of information in uav assisted networks"
    - "3d trajectory optimization in rician fading for uav enabled data harvesting"
    - "path design for cellular connected uav with reinforcement learning"
    - "local map assisted positioning for flying wireless relays"
    - "learning to communicate in uav aided wireless networks map based approaches"

Connected through hyperedge HE-5 (induced by source paper "a reinforcement learning framework for optimizing age of information in rf powered communication systems"):
  with members:
    - "average peak age of information minimization in uav assisted iot networks"
    - "timely updates in energy harvesting two hop networks offline and online policies"
    - "ultra reliable low latency vehicular networks taming the age of information tail"
    - "sending information through status updates"
    - "optimal status update for age of information minimization with an energy harvesting source"
    - "timely updates over an erasure channel"
    - "age and value of information non linear age case"
    - "update or wait how to keep your data fresh"

Connected through hyperedge HE-6 (induced by source paper "deep reinforcement learning for minimizing age of information in uav assisted networks"):
  with members:
    - "optimized path planning for inspection by unmanned aerial vehicles swarm with energy constraints"
    - "ultra reliable low latency vehicular networks taming the age of information tail"
    - "machine learning for wireless connectivity and security of cellular connected uavs"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "throughput maximization for uav enabled wireless powered communication networks"
    - "optimizing age of information in wireless networks with perfect channel state information"
    - "average age of information with hybrid arq under a resource constraint"
    - "update or wait how to keep your data fresh"

Connected through hyperedge HE-7 (induced by source paper "probability analysis of age of information in multi hop networks"):
  with members:
    - "a general formula for the stationary distribution of the age of information and its application to single server queues"
    - "age of information vs value of information scheduling for cellular networked control systems"
    - "performance characterization using aoi in a single loop networked control system"
    - "age of information in a network of preemptive servers"
    - "age optimal information updates in multihop networks"
    - "status updates over unreliable multiaccess channels"
    - "update or wait how to keep your data fresh"
    - "on the age of information in status update systems with packet management"

Connected through hyperedge HE-8 (induced by source paper "age optimal information gathering and dissemination on graphs"):
  with members:
    - "optimizing information freshness in wireless networks under general interference constraints"
    - "update or wait how to keep your data fresh"
    - "persistent monitoring in discrete environments minimizing the maximum weighted latency between observations"
    - "an optimal control approach for the persistent monitoring problem"

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.IT(Information Theory)