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 "efficient deployment and mission timing of autonomous underwater vehicles in large scale operations"):
  Abstract: This study introduces a connective model of routing -- local path planning for Autonomous Underwater Vehicle (AUV) time efficient maneuver in long-range operations. Assuming the vehicle operating in a turbulent underwater environment, the local path planner produces the water-current resilient shortest paths along the existent nodes in the global route. A re-routing procedure is defined to re-organize the order of nodes in a route and compensate any lost time during the mission. The Firefly Optimization Algorithm (FOA) is conducted by both of the planners to validate the model's performance in mission timing and its robustness against water current variations. Considering the limitation over the battery life time, the model offers an accurate mission timing and real-time performance. The routing system and the local path planner operate cooperatively, and this is another reason for model's real-time performance. The simulation results confirms the model's capability in fulfillment of the expected criterion and proves its significant robustness against underwater uncertainties and variations of the mission conditions.

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 "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 "a novel versatile architecture for autonomous underwater vehicle s motion planning and task assignment")
  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 "a novel versatile architecture for autonomous underwater vehicle s motion planning and task assignment")
  Member "optimal route planning with prioritized task scheduling for auv missions":
    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")

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)