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: "optimal route planning with prioritized task scheduling for auv missions"
  Abstract: This paper presents a solution to Autonomous Underwater Vehicles (AUVs) large scale route planning and task assignment joint problem. Given a set of constraints (e.g., time) and a set of task priority values, the goal is to find the optimal route for underwater mission that maximizes the sum of the priorities and minimizes the total risk percentage while meeting the given constraints. Making use of the heuristic nature of genetic and swarm intelligence algorithms in solving NP-hard graph problems, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are employed to find the optimum solution, where each individual in the population is a candidate solution (route). To evaluate the robustness of the proposed methods, the performance of the all PS and GA algorithms are examined and compared for a number of Monte Carlo runs. Simulation results suggest that the routes generated by both algorithms are feasible and reliable enough, and applicable for underwater motion planning. However, the GA-based route planner produces superior results comparing to the results obtained from the PSO based route planner.

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"
    - "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"

Connected through hyperedge HE-2 (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"
    - "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"

Connected through hyperedge HE-3 (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"
    - "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"

Connected through hyperedge HE-4 (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"
    - "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"

Connected through hyperedge HE-5 (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"
    - "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"

Connected through hyperedge HE-6 (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"
    - "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"

Connected through hyperedge HE-7 (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"
    - "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"

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"
    - "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"

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)