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 "cooperative and distributed reinforcement learning of drones for field coverage"):
  Abstract: This paper proposed a distributed Multi-Agent Reinforcement Learning (MARL) algorithm for a team of Unmanned Aerial Vehicles (UAVs) that can learn to cooperate to provide a full coverage of an unknown field of interest while minimizing the overlapping sections among their field of views. Two challenges in MARL for such a system are discussed in the paper: firstly, the complex dynamic of the joint-actions of the UAV team, that will be solved using game-theoretic correlated equilibrium, and secondly, the challenge in huge dimensional state space will be tackled with an efficient space-reduced representation of the value function table. We also provided our experimental results in details with both simulation and physical implementation to show that the UAVs can successfully learn to accomplish the task without the need of a mathematical model. This paper can serve as an efficient framework for using MARL to enable UAV team to work in an environment where its model is unavailable. In the future, we are interested in accounting for the stochastic aspect of the problem and technical aspects of a real-world deployment, where uncertainties, such as wind and other dynamics of the environment presents.

Includes members:
  Member "autonomous uav navigation using reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "communication efficient massive uav online path control federated learning meets mean field game theory")
  Member "a distributed control framework for a team of unmanned aerial vehicles for dynamic wildfire tracking":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "safe coordination of human robot firefighting teams")
  Member "multi robot transfer learning a dynamical system perspective":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "knowledge transfer between robots with similar dynamics for high accuracy impromptu trajectory tracking")
  Member "safe multi agent reinforcement learning for autonomous driving":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep reinforcement learning for autonomous driving a survey")

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)