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: "an efficient hybrid route path planning model for dynamic task allocation and safe maneuvering of an underwater vehicle in a realistic environment"
  Abstract: This paper presents a hybrid route-path planning model for an Autonomous Underwater Vehicle's task assignment and management while the AUV is operating through the variable littoral waters. Several prioritized tasks distributed in a large scale terrain is defined first; then, considering the limitations over the mission time, vehicle's battery, uncertainty and variability of the underlying operating field, appropriate mission timing and energy management is undertaken. The proposed objective is fulfilled by incorporating a route-planner that is in charge of prioritizing the list of available tasks according to available battery and a path-planer that acts in a smaller scale to provide vehicle's safe deployment against environmental sudden changes. The synchronous process of the task assign-route and path planning is simulated using a specific composition of Differential Evolution and Firefly Optimization (DEFO) Algorithms. The simulation results indicate that the proposed hybrid model offers efficient performance in terms of completion of maximum number of assigned tasks while perfectly expending the minimum energy, provided by using the favorable current flow, and controlling the associated mission time. The Monte-Carlo test is also performed for further analysis. The corresponding results show the significant robustness of the model against uncertainties of the operating field and variations of mission conditions.

Connected through hyperedge HE-1 (induced by source paper "efficient deployment and mission timing of autonomous underwater vehicles in large scale operations"):
  with members:
    - "a novel versatile architecture for autonomous underwater vehicle s motion planning and task assignment"
    - "differential evolution for efficient auv path planning in time variant uncertain underwater environment"
    - "a hierarchal planning framework for auv mission management in a spatio temporal varying ocean"
    - "optimal route planning with prioritized task scheduling for auv missions"

Connected through hyperedge HE-2 (induced by source paper "development of an autonomous reactive mission scheduling and path planning armsp architecture using evolutionary algorithms for auv operation in a sever ocean environment"):
  with members:
    - "a novel versatile architecture for autonomous underwater vehicle s motion planning and task assignment"
    - "auv rendezvous online path planning in a highly cluttered undersea environment using evolutionary algorithms"
    - "an autonomous reactive architecture for efficient auv mission time management in realistic severe ocean environment"
    - "a novel efficient task assign route planning method for auv guidance in a dynamic cluttered environment"
    - "biogeography based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task time management"
    - "differential evolution for efficient auv path planning in time variant uncertain underwater environment"
    - "toward efficient task assignment and motion planning for large scale underwater mission"
    - "optimal route planning with prioritized task scheduling for auv missions"

Connected through hyperedge HE-3 (induced by source paper "an autonomous reactive architecture for efficient auv mission time management in realistic severe ocean environment"):
  with members:
    - "a novel versatile architecture for autonomous underwater vehicle s motion planning and task assignment"
    - "auv rendezvous online path planning in a highly cluttered undersea environment using evolutionary algorithms"
    - "a novel efficient task assign route planning method for auv guidance in a dynamic cluttered environment"
    - "biogeography based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task time management"
    - "differential evolution for efficient auv path planning in time variant uncertain underwater environment"
    - "toward efficient task assignment and motion planning for large scale underwater mission"
    - "optimal route planning with prioritized task scheduling for auv missions"

Connected through hyperedge HE-4 (induced by source paper "a hierarchal planning framework for auv mission management in a spatio temporal varying ocean"):
  with members:
    - "a novel versatile architecture for autonomous underwater vehicle s motion planning and task assignment"
    - "auv rendezvous online path planning in a highly cluttered undersea environment using evolutionary algorithms"
    - "a novel efficient task assign route planning method for auv guidance in a dynamic cluttered environment"
    - "biogeography based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task time management"
    - "differential evolution for efficient auv path planning in time variant uncertain underwater environment"
    - "toward efficient task assignment and motion planning for large scale underwater mission"
    - "optimal route planning with prioritized task scheduling for auv missions"

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)