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 "development of an autonomous reactive mission scheduling and path planning armsp architecture using evolutionary algorithms for auv operation in a sever ocean environment"):
  Abstract: Providing a higher level of decision autonomy is a true challenge in development of today AUVs and promotes a single vehicle to accomplish multiple tasks in a single mission as well as accompanying prompt changes of a turbulent and highly uncertain environment, which has not been completely attained yet. The proceeding approach builds on recent researches toward constructing a comprehensive structure for AUV mission planning, routing, task-time managing and synchronic online motion planning adaptive to sudden changes of the time variant environment. Respectively, an "Autonomous Reactive Mission Scheduling and Path Planning" (ARMSP) architecture is constructed in this paper and a bunch of evolutionary algorithms are employed by different layers of the proposed control architecture to investigate the efficiency of the structure toward handling addressed objectives and prove stability of its performance in real-time mission task-time-threat management regardless of the applied metaheuristic algorithm. Static current map data, uncertain dynamic-static obstacles, vehicles Kino-dynamic constraints are taken into account and online path re-planning strategy is adopted to consider local variations of the environment so that a small computational load is devoted for re-planning procedure since the upper layer, which is responsible for mission scheduling, renders an overview of the operation area that AUV should fly thru. Numerical simulations for analysis of different situations of the real-world environment is accomplished separately for each layer and also for the entire ARMSP model at the end. Performance and stability of the model is investigated thorough employing metaheuristic algorithms toward furnishing the stated mission goals.

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 "auv rendezvous online path planning in a highly cluttered undersea environment using evolutionary algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "person following by autonomous robots a categorical overview")
  Member "an autonomous reactive architecture for efficient auv mission time management in realistic severe ocean environment":
    also connected through other hyperedges:
      (none)
  Member "an efficient hybrid route path planning model for dynamic task allocation and safe maneuvering of an underwater vehicle in a realistic environment":
    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 "a novel efficient task assign route planning method for auv guidance in a dynamic cluttered environment":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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-5 (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-6 (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-7 (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)