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: "friend collaborator student manager how design of an ai driven game level editor affects creators"
  Abstract: Machine learning advances have afforded an increase in algorithms capable of creating art, music, stories, games, and more. However, it is not yet well-understood how machine learning algorithms might best collaborate with people to support creative expression. To investigate how practicing designers perceive the role of AI in the creative process, we developed a game level design tool for Super Mario Bros.-style games with a built-in AI level designer. In this paper we discuss our design of the Morai Maker intelligent tool through two mixed-methods studies with a total of over one-hundred participants. Our findings are as follows: (1) level designers vary in their desired interactions with, and role of, the AI, (2) the AI prompted the level designers to alter their design practices, and (3) the level designers perceived the AI as having potential value in their design practice, varying based on their desired role for the AI.

Connected through hyperedge HE-1 (induced by source paper "machine learning based co creative design framework"):
  with members:
    - "toward a neuro inspired creative decoder"
    - "design design inspiration from generative networks"
    - "co creative level design via machine learning"
    - "outfit generation and style extraction via bidirectional lstm and autoencoder"
    - "styling with attention to details"
    - "generative image inpainting with contextual attention"
    - "can creative adversarial networks generating art by learning about styles and deviating from style norms"
    - "progressive growing of gans for improved quality stability and variation"

Connected through hyperedge HE-2 (induced by source paper "an interaction framework for studying co creative ai"):
  with members:
    - "automated rationale generation a technique for explainable ai and its effects on human perceptions"
    - "co creative level design via machine learning"
    - "explainable pcgml via game design patterns"
    - "evaluating creativity in computational co creative systems"
    - "bringing impressionism to life with neural style transfer in come swim"
    - "event representations for automated story generation with deep neural nets"
    - "procedural content generation via machine learning pcgml"
    - "statistical parametric speech synthesis incorporating generative adversarial networks"

Connected through hyperedge HE-3 (induced by source paper "coevo a collaborative design platform with artificial agents"):
  with members:
    - "creative ai through evolutionary computation"
    - "the surprising creativity of digital evolution a collection of anecdotes from the evolutionary computation and artificial life research communities"
    - "a hierarchical latent vector model for learning long term structure in music"
    - "a neural representation of sketch drawings"
    - "robots that can adapt like animals"
    - "the arcade learning environment an evaluation platform for general agents"

Connected through hyperedge HE-4 (induced by source paper "deep learning in a computational model for conceptual shifts in a co creative design system"):
  with members:
    - "deep learning for identifying potential conceptual shifts for co creative drawing"
    - "evaluating creativity in computational co creative systems"
    - "a neural representation of sketch drawings"
    - "very deep convolutional networks for large scale image recognition"

Connected through hyperedge HE-5 (induced by source paper "integrating automated play in level co creation"):
  with members:
    - "co creative level design via machine learning"
    - "general video game ai a multi track framework for evaluating agents games and content generation algorithms"
    - "procedural content generation via machine learning pcgml"

Connected through hyperedge HE-6 (induced by source paper "evaluation of a recommender system for assisting novice game designers"):
  with members:
    - "pitako recommending game design elements in cicero"

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.HC(Human-Computer Interaction)