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: "helping ai to play hearthstone aaia 17 data mining challenge"
  Abstract: This paper summarizes the AAIA'17 Data Mining Challenge: Helping AI to Play Hearthstone which was held between March 23, and May 15, 2017 at the Knowledge Pit platform. We briefly describe the scope and background of this competition in the context of a more general project related to the development of an AI engine for video games, called Grail. We also discuss the outcomes of this challenge and demonstrate how predictive models for the assessment of player's winning chances can be utilized in a construction of an intelligent agent for playing Hearthstone. Finally, we show a few selected machine learning approaches for modeling state and action values in Hearthstone. We provide evaluation for a few promising solutions that may be used to create more advanced types of agents, especially in conjunction with Monte Carlo Tree Search algorithms.

Connected through hyperedge HE-1 (induced by source paper "the many ai challenges of hearthstone"):
  with members:
    - "mapping hearthstone deck spaces through map elites with sliding boundaries"
    - "evolving the hearthstone meta"
    - "co creative level design via machine learning"
    - "improving hearthstone ai by combining mcts and supervised learning algorithms"
    - "atdelfi automatically designing legible full instructions for games"
    - "automated playtesting with procedural personas through mcts with evolved heuristics"
    - "latent predictor networks for code generation"
    - "robots that can adapt like animals"

Connected through hyperedge HE-2 (induced by source paper "mapping hearthstone deck spaces through map elites with sliding boundaries"):
  with members:
    - "monte carlo tree search for simulation based strategy analysis"
    - "talakat bullet hell generation through constrained map elites"
    - "q deckrec a fast deck recommendation system for collectible card games"
    - "improving hearthstone ai by combining mcts and supervised learning algorithms"
    - "demonstrating the feasibility of automatic game balancing"
    - "robots that can adapt like animals"
    - "evolving a behavioral repertoire for a walking robot"

Connected through hyperedge HE-3 (induced by source paper "improving hearthstone ai by combining mcts and supervised learning algorithms"):
  with members:
    - "mastering chess and shogi by self play with a general reinforcement learning algorithm"
    - "distributed representations of sentences and documents"
    - "distributed representations of words and phrases and their compositionality"

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)