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: "effect of shapes of activation functions on predictability in the echo state network"
  Abstract: We investigate prediction accuracy for time series of Echo state networks with respect to several kinds of activation functions. As a result, we found that some kinds of activation functions with an appropriate nonlinearity show high performance compared to the conventional sigmoid function.

Connected through hyperedge HE-1 (induced by source paper "reinforcement learning with convolutional reservoir computing"):
  with members:
    - "weight agnostic neural networks"
    - "distributive dynamic spectrum access through deep reinforcement learning a reservoir computing based approach"
    - "deep neuroevolution of recurrent and discrete world models"
    - "distributed prioritized experience replay"
    - "recurrent world models facilitate policy evolution"
    - "deep reinforcement learning a brief survey"
    - "vizdoom a doom based ai research platform for visual reinforcement learning"
    - "asynchronous methods for deep reinforcement learning"

Connected through hyperedge HE-2 (induced by source paper "convolutional reservoir computing for world models"):
  with members:
    - "deep neuroevolution of recurrent and discrete world models"
    - "learning latent dynamics for planning from pixels"
    - "world models"
    - "distributed prioritized experience replay"
    - "recurrent world models facilitate policy evolution"
    - "deep reinforcement learning a brief survey"
    - "asynchronous methods for deep reinforcement learning"
    - "the cma evolution strategy a tutorial"

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.NE(Neural and Evolutionary Computing)