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 "learning cooperative games"):
  Abstract: This paper explores a PAC (probably approximately correct) learning model in cooperative games. Specifically, we are given $m$ random samples of coalitions and their values, taken from some unknown cooperative game; can we predict the values of unseen coalitions? We study the PAC learnability of several well-known classes of cooperative games, such as network flow games, threshold task games, and induced subgraph games. We also establish a novel connection between PAC learnability and core stability: for games that are efficiently learnable, it is possible to find payoff divisions that are likely to be stable using a polynomial number of samples.

Includes members:
  Member "coalition games on interaction graphs a horticultural perspective":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "computing stable coalitions approximation algorithms for reward sharing")
  Member "solving cooperative reliability games":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "attacking power indices by manipulating player reliability")
  Member "learning valuation functions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "powerset convolutional neural networks")
  Member "cooperative games with overlapping coalitions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "dynamic network slicing for scalable fog computing systems with energy harvesting")
  Member "introduction to machine learning class notes 67577":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "scalable and compact 3d action recognition with approximated rbf kernel machines")
  Member "the cost of stability in coalitional games":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "computing the value of spatio temporal data in wholesale and retail data marketplaces")

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.GT(Computer Science and Game Theory)