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 "addressing the fundamental tension of pcgml with discriminative learning"):
  Abstract: Procedural content generation via machine learning (PCGML) is typically framed as the task of fitting a generative model to full-scale examples of a desired content distribution. This approach presents a fundamental tension: the more design effort expended to produce detailed training examples for shaping a generator, the lower the return on investment from applying PCGML in the first place. In response, we propose the use of discriminative models (which capture the validity of a design rather the distribution of the content) trained on positive and negative examples. Through a modest modification of WaveFunctionCollapse, a commercially-adopted PCG approach that we characterize as using elementary machine learning, we demonstrate a new mode of control for learning-based generators. We demonstrate how an artist might craft a focused set of additional positive and negative examples by critique of the generator's previous outputs. This interaction mode bridges PCGML with mixed-initiative design assistance tools by working with a machine to define a space of valid designs rather than just one new design.

Includes members:
  Member "co creative level design via machine learning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "machine learning based co creative design framework")
  Member "evolving mario levels in the latent space of a deep convolutional generative adversarial network":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "increasing generality in machine learning through procedural content generation")
  Member "explainable pcgml via game design patterns":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "controllable level blending between games using variational autoencoders")
  Member "automatic mapping of nes games with mappy":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "conceptual game expansion")
  Member "procedural content generation via machine learning pcgml":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "increasing generality in machine learning through procedural content generation")
  Member "the vglc the video game level corpus":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "controllable level blending between games using variational autoencoders")
  Member "super mario as a string platformer level generation via lstms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "increasing generality in machine learning through procedural content generation")
  Member "clingo asp control preliminary report":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "the external interface for extending wasp")

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.LG(Machine Learning)