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: "pseudorehearsal in value function approximation"
  Abstract: Catastrophic forgetting is of special importance in reinforcement learning, as the data distribution is generally non-stationary over time. We study and compare several pseudorehearsal approaches for Q-learning with function approximation in a pole balancing task. We have found that pseudorehearsal seems to assist learning even in such very simple problems, given proper initialization of the rehearsal parameters.

Connected through hyperedge HE-1 (induced by source paper "pseudo rehearsal achieving deep reinforcement learning without catastrophic forgetting"):
  with members:
    - "continual state representation learning for reinforcement learning using generative replay"
    - "progressive reinforcement learning with distillation for multi skilled motion control"
    - "experience replay for continual learning"
    - "two geometric input transformation methods for fast online reinforcement learning with neural nets"
    - "learning to learn without forgetting by maximizing transfer and minimizing interference"
    - "deep generative dual memory network for continual learning"
    - "pseudo recursal solving the catastrophic forgetting problem in deep neural networks"
    - "selective experience replay for lifelong learning"

Connected through hyperedge HE-2 (induced by source paper "pseudorehearsal in actor critic agents with neural network function approximation"):
  with members:
    - "overcoming catastrophic forgetting in neural networks"
    - "a cognitive architecture for the implementation of emotions in computing systems"

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.AI(Artificial Intelligence)