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: "game ai research with fast planet wars variants"
  Abstract: This paper describes a new implementation of Planet Wars, designed from the outset for Game AI research. The skill-depth of the game makes it a challenge for game-playing agents, and the speed of more than 1 million game ticks per second enables rapid experimentation and prototyping. The parameterised nature of the game together with an interchangeable actuator model make it well suited to automated game tuning. The game is designed to be fun to play for humans, and is directly playable by General Video Game AI agents.

Connected through hyperedge HE-1 (induced by source paper "efficient evolutionary methods for game agent optimisation model based is best"):
  with members:
    - "the n tuple bandit evolutionary algorithm for game agent optimisation"
    - "general video game ai a multi track framework for evaluating agents games and content generation algorithms"
    - "the n tuple bandit evolutionary algorithm for automatic game improvement"
    - "bandit based random mutation hill climbing"

Connected through hyperedge HE-2 (induced by source paper "toybox better atari environments for testing reinforcement learning agents"):
  with members:
    - "let s play again variability of deep reinforcement learning agents in atari environments"
    - "terrain rl simulator"
    - "distributed evaluations ending neural point metrics"
    - "elf an extensive lightweight and flexible research platform for real time strategy games"
    - "deep reinforcement learning a brief survey"
    - "starcraft ii a new challenge for reinforcement learning"
    - "can deep reinforcement learning solve erdos selfridge spencer games"
    - "control of a quadrotor with reinforcement learning"

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)