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: "faster and simpler algorithm for optimal strategies of blotto game"
  Abstract: In the Colonel Blotto game, which was initially introduced by Borel in 1921, two colonels simultaneously distribute their troops across different battlefields. The winner of each battlefield is determined independently by a winner-take-all rule. The ultimate payoff of each colonel is the number of battlefields he wins. This game is commonly used for analyzing a wide range of applications such as the U.S presidential election, innovative technology competitions, advertisements, etc. There have been persistent efforts for finding the optimal strategies for the Colonel Blotto game. After almost a century Ahmadinejad, Dehghani, Hajiaghayi, Lucier, Mahini, and Seddighin provided a poly-time algorithm for finding the optimal strategies. They first model the problem by a Linear Program (LP) and use Ellipsoid method to solve it. However, despite the theoretical importance of their algorithm, it is highly impractical. In general, even Simplex method (despite its exponential running-time) performs better than Ellipsoid method in practice. In this paper, we provide the first polynomial-size LP formulation of the optimal strategies for the Colonel Blotto game. We use linear extension techniques. Roughly speaking, we project the strategy space polytope to a higher dimensional space, which results in a lower number of facets for the polytope. We use this polynomial-size LP to provide a novel, simpler and significantly faster algorithm for finding the optimal strategies for the Colonel Blotto game. We further show this representation is asymptotically tight in terms of the number of constraints. We also extend our approach to multi-dimensional Colonel Blotto games, and implement our algorithm to observe interesting properties of Colonel Blotto; for example, we observe the behavior of players in the discrete model is very similar to the previously studied continuous model.

Connected through hyperedge HE-1 (induced by source paper "the multiplayer colonel blotto game"):
  with members:
    - "optimal strategies of blotto games beyond convexity"

Connected through hyperedge HE-2 (induced by source paper "computing stackelberg equilibria of large general sum games"):
  with members:
    - "a polynomial time algorithm for spatio temporal security games"
    - "security game with non additive utilities and multiple attacker resources"
    - "oracle efficient online learning and auction design"
    - "the mysteries of security games equilibrium computation becomes combinatorial algorithm design"
    - "catcher evader games"
    - "bilinear games polynomial time algorithms for rank based subclasses"

Connected through hyperedge HE-3 (induced by source paper "approximate equilibria in non constant sum colonel blotto and lottery blotto games with large numbers of battlefields"):
  with members:
    - "defensive resource allocation in social networks"
    - "a colonel blotto gladiator game"

Connected through hyperedge HE-4 (induced by source paper "optimal strategies of blotto games beyond convexity"):
  with members:
    - "from duels to battefields computing equilibria of blotto and other games"

Connected through hyperedge HE-5 (induced by source paper "a polynomial time algorithm for spatio temporal security games"):
  with members:
    - "machine learning techniques for stackelberg security games a survey"
    - "from duels to battefields computing equilibria of blotto and other games"
    - "the mysteries of security games equilibrium computation becomes combinatorial algorithm design"

Connected through hyperedge HE-6 (induced by source paper "from duels to battefields computing equilibria of blotto and other games"):
  with members:
    - "price of competition and dueling games"
    - "the matching polytope has exponential extension complexity"
    - "bilinear games polynomial time algorithms for rank based subclasses"
    - "polynomial time computation of exact correlated equilibrium in compact games"
    - "computing nash equilibria approximation and smoothed complexity"

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.GT(Computer Science and Game Theory)