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: "differential evolution for efficient auv path planning in time variant uncertain underwater environment"
  Abstract: The AUV three-dimension path planning in complex turbulent underwater environment is investigated in this research, in which static current map data and uncertain static-moving time variant obstacles are taken into account. Robustness of AUVs path planning to this strong variability is known as a complex NP-hard problem and is considered a critical issue to ensure vehicles safe deployment. Efficient evolutionary techniques have substantial potential of handling NP hard complexity of path planning problem as more powerful and fast algorithms among other approaches for mentioned problem. For the purpose of this research Differential Evolution (DE) technique is conducted to solve the AUV path planning problem in a realistic underwater environment. The path planners designed in this paper are capable of extracting feasible areas of a real map to determine the allowed spaces for deployment, where coastal area, islands, static/dynamic obstacles and ocean current is taken into account and provides the efficient path with a small computation time. The results obtained from analyze of experimental demonstrate the inherent robustness and drastic efficiency of the proposed scheme in enhancement of the vehicles path planning capability in coping undesired current, using useful current flow, and avoid colliding collision boundaries in a real-time manner. The proposed approach is also flexible and strictly respects to vehicle's kinematic constraints resisting current instabilities.

Connected through hyperedge HE-1 (induced by source paper "a novel versatile architecture for autonomous underwater vehicle s motion planning and task assignment"):
  with members:
    - "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"
    - "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-2 (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"
    - "an efficient hybrid route path planning model for dynamic task allocation and safe maneuvering of an underwater vehicle in a realistic 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-3 (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"
    - "an efficient hybrid route path planning model for dynamic task allocation and safe maneuvering of an underwater vehicle in a realistic 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"
    - "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 "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"
    - "an efficient hybrid route path planning model for dynamic task allocation and safe maneuvering of an underwater vehicle in a realistic 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"
    - "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-5 (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"
    - "an efficient hybrid route path planning model for dynamic task allocation and safe maneuvering of an underwater vehicle in a realistic 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"
    - "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-6 (induced by source paper "an efficient hybrid route path planning model for dynamic task allocation and safe maneuvering of an underwater vehicle in a realistic 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"
    - "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-7 (induced by source paper "auv rendezvous online path planning in a highly cluttered undersea environment using evolutionary algorithms"):
  with members:
    - "a novel versatile architecture for autonomous underwater vehicle s motion planning and task assignment"
    - "real time quasi optimal trajectory planning for autonomous underwater docking"
    - "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"
    - "toward efficient task assignment and motion planning for large scale underwater mission"

Connected through hyperedge HE-8 (induced by source paper "biogeography based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task time management"):
  with members:
    - "a novel efficient task assign route planning method for auv guidance in a dynamic cluttered 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)