human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "auv rendezvous online path planning in a highly cluttered undersea environment using evolutionary algorithms"):
  Abstract: In this study, a single autonomous underwater vehicle (AUV) aims to rendezvous with a submerged leader recovery vehicle through a cluttered and variable operating field. The rendezvous problem is transformed into a nonlinear optimal control problem (NOCP) and then numerical solutions are provided. A penalty function method is utilized to combine the boundary conditions, vehicular and environmental constraints with the performance index that is final rendezvous time.Four evolutionary based path planning methods namely particle swarm optimization (PSO), biogeography-based optimization (BBO), differential evolution (DE) and Firefly algorithm (FA) are employed to establish a reactive planner module and provide a numerical solution for the proposed NOCP. The objective is to synthesize and analysis the performance and capability of the mentioned methods for guiding an AUV from loitering point toward the rendezvous place through a comprehensive simulation study.The proposed planner module entails a heuristic for refining the path considering situational awareness of underlying environment, encompassing static and dynamic obstacles overwhelmed in spatiotemporal current vectors.This leads to accommodate the unforeseen changes in the operating field like emergence of unpredicted obstacles or variability of current vector filed and turbulent regions. The simulation results demonstrate the inherent robustness and significant efficiency of the proposed planner in enhancement of the vehicle's autonomy in terms of using current force, coping undesired current disturbance for the desired rendezvous purpose. Advantages and shortcoming of all utilized methods are also presented based on the obtained results.

Includes members:
  Member "a novel versatile architecture for autonomous underwater vehicle s motion planning and task assignment":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "efficient deployment and mission timing of autonomous underwater vehicles in large scale operations")
  Member "real time quasi optimal trajectory planning for autonomous underwater docking":
    also connected through other hyperedges:
      (none)
  Member "a novel efficient task assign route planning method for auv guidance in a dynamic cluttered environment":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficient deployment and mission timing of autonomous underwater vehicles in large scale operations")
  Member "biogeography based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task time management":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "efficient deployment and mission timing of autonomous underwater vehicles in large scale operations")
  Member "differential evolution for efficient auv path planning in time variant uncertain underwater environment":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a novel versatile architecture for autonomous underwater vehicle s motion planning and task assignment")
  Member "toward efficient task assignment and motion planning for large scale underwater mission":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a novel versatile architecture for autonomous underwater vehicle s motion planning and task assignment")

Question: Please tell me which class the source paper 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)