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: "ai researchers video games are your friends"
  Abstract: Artificial intelligence and games go way back. At least to Turing, who re-invented the Minimax algorithm to play Chess even before he had a computer, and to Samuel, who invented a predecessor of TD-learning in order to build a Checkers-playing program in the 1950s. Games are important for AI because they are designed to challenge and train human cognitive capabilities, and are thus uniquely relevant benchmark problems. They are also uniquely convenient benchmark problems, as they allow unbiased comparison between algorithms and can be executed thousands of times fast than realtime. But one should also not forget the financial clout of the games industry and games' appeal for new students. While research on board games such as Chess and Go has been part of AI research since its inception, the last decade has seen the rise of a research community around AI for video games, and not only for playing them. In this talk I will outline some of the most important trends in recent years. One is General Video Game Playing: developing controllers that can learn to play not just a single game, but a large variety variety of them. Another is Procedural Content Generation, where AI algorithms are used to generate content for games, or even design the games themselves. Yet another trend is AI-assisted design tools, which provide the game designer with instant feedback and suggestions and thus scaffolds the game design process. These research topics inform each other, with general video game playing algorithms being important for procedural content generation and AI-assisted design tools. Finally, I will try to convince you that your own research is important for this endeavor and that you should consider steering your research towards AI for games.

Connected through hyperedge HE-1 (induced by source paper "ludii as a competition platform"):
  with members:
    - "general video game rule generation"
    - "an empirical evaluation of two general game systems ludii and rbg"
    - "prolonets neural encoding human experts domain knowledge to warm start reinforcement learning"
    - "ludii the ludemic general game system"
    - "an overview of the ludii general game system"
    - "the 2017 aibirds competition"
    - "atdelfi automatically designing legible full instructions for games"
    - "deceptive games"

Connected through hyperedge HE-2 (induced by source paper "the text based adventure ai competition"):
  with members:
    - "deep reinforcement learning that matters"
    - "curiosity driven exploration by self supervised prediction"
    - "revisiting the arcade learning environment evaluation protocols and open problems for general agents"
    - "text based adventures of the golovin ai agent"
    - "what can you do with a rock affordance extraction via word embeddings"
    - "bag of tricks for efficient text classification"
    - "skip thought vectors"
    - "language understanding for text based games using deep reinforcement learning"

Connected through hyperedge HE-3 (induced by source paper "the 2017 aibirds competition"):
  with members:
    - "deep learning for video game playing"
    - "vizdoom a doom based ai research platform for visual reinforcement learning"
    - "a bayesian ensemble regression framework on the angry birds game"
    - "towards a theory of mind inspired generic decision making framework"

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)