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: "rolling horizon coevolutionary planning for two player video games"
  Abstract: This paper describes a new algorithm for decision making in two-player real-time video games. As with Monte Carlo Tree Search, the algorithm can be used without heuristics and has been developed for use in general video game AI. The approach is to extend recent work on rolling horizon evolutionary planning, which has been shown to work well for single-player games, to two (or in principle many) player games. To select an action the algorithm co-evolves two (or in the general case N) populations, one for each player, where each individual is a sequence of actions for the respective player. The fitness of each individual is evaluated by playing it against a selection of action-sequences from the opposing population. When choosing an action to take in the game, the first action is chosen from the fittest member of the population for that player. The new algorithm is compared with a number of general video game AI algorithms on three variations of a two-player space battle game, with promising results.

Connected through hyperedge HE-1 (induced by source paper "the n tuple bandit evolutionary algorithm for game agent optimisation"):
  with members:
    - "analysis of vanilla rolling horizon evolution parameters in general video game playing"
    - "population seeding techniques for rolling horizon evolution in general video game playing"
    - "the n tuple bandit evolutionary algorithm for automatic game improvement"
    - "evolving game skill depth using general video game ai agents"
    - "efficient hyperparameter optimization and infinitely many armed bandits"
    - "population based training of neural networks"
    - "hyperband a novel bandit based approach to hyperparameter optimization"
    - "bandit based random mutation hill climbing"

Connected through hyperedge HE-2 (induced by source paper "intelligent middle level game control"):
  with members:
    - "population seeding techniques for rolling horizon evolution in general video game playing"
    - "proximal policy optimization algorithms"

Connected through hyperedge HE-3 (induced by source paper "evolving game skill depth using general video game ai agents"):
  with members:
    - "the n tuple bandit evolutionary algorithm for automatic game improvement"
    - "bandit based random mutation hill climbing"
    - "optimal resampling for the noisy onemax problem"

Connected through hyperedge HE-4 (induced by source paper "population seeding techniques for rolling horizon evolution in general video game playing"):
  with members:
    - "analysis of vanilla rolling horizon evolution parameters in general video game playing"
    - "the arcade learning environment an evaluation platform for general agents"

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)