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 "badger learning to learn learning algorithms through multi agent communication"):
  Abstract: In this work, we propose a novel memory-based multi-agent meta-learning architecture and learning procedure that allows for learning of a shared communication policy that enables the emergence of rapid adaptation to new and unseen environments by learning to learn learning algorithms through communication. Behavior, adaptation and learning to adapt emerges from the interactions of homogeneous experts inside a single agent. The proposed architecture should allow for generalization beyond the level seen in existing methods, in part due to the use of a single policy shared by all experts within the agent as well as the inherent modularity of 'Badger'.

Includes members:
  Member "backpropamine training self modifying neural networks with differentiable neuromodulated plasticity":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "finding online neural update rules by learning to remember")
  Member "efficient optimization of loops and limits with randomized telescoping sums":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "scheduling the learning rate via hypergradients new insights and a new algorithm")
  Member "ai gas ai generating algorithms an alternate paradigm for producing general artificial intelligence":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "meta learning curiosity algorithms")
  Member "meta learning of sequential strategies":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "differentiable bandit exploration")
  Member "modularity as a means for complexity management in neural networks learning":
    also connected through other hyperedges:
      (none)
  Member "a mathematical theory of cooperative communication":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sequential cooperative bayesian inference")
  Member "learning to communicate in multi agent reinforcement learning a review":
    also connected through other hyperedges:
      (none)
  Member "mastering atari go chess and shogi by planning with a learned model":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "neuroevolution of self interpretable agents")

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.AI(Artificial Intelligence)