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: "cops and invisible robbers the cost of drunkenness"
  Abstract: We examine a version of the Cops and Robber (CR) game in which the robber is invisible, i.e., the cops do not know his location until they capture him. Apparently this game (CiR) has received little attention in the CR literature. We examine two variants: in the first the robber is adversarial (he actively tries to avoid capture); in the second he is drunk (he performs a random walk). Our goal in this paper is to study the invisible Cost of Drunkenness (iCOD), which is defined as the ratio ct_i(G)/dct_i(G), with ct_i(G) and dct_i(G) being the expected capture times in the adversarial and drunk CiR variants, respectively. We show that these capture times are well defined, using game theory for the adversarial case and partially observable Markov decision processes (POMDP) for the drunk case. We give exact asymptotic values of iCOD for several special graph families such as $d$-regular trees, give some bounds for grids, and provide general upper and lower bounds for general classes of graphs. We also give an infinite family of graphs showing that iCOD can be arbitrarily close to any value in [2,infinty). Finally, we briefly examine one more CiR variant, in which the robber is invisible and "infinitely fast"; we argue that this variant is significantly different from the Graph Search game, despite several similarities between the two games.

Connected through hyperedge HE-1 (induced by source paper "selfish cops and active robber multi player pursuit evasion on graphs"):
  with members:
    - "generalized cops and robbers a multi player pursuit game on graphs"
    - "selfish cops and passive robber qualitative games"
    - "simultaneously moving cops and robbers"
    - "the role of visibility in pursuit evasion games"

Connected through hyperedge HE-2 (induced by source paper "selfish cops and passive robber part i qualitative games"):
  with members:
    - "simultaneously moving cops and robbers"
    - "the role of visibility in pursuit evasion games"
    - "cops and robbers game theory and zermelo s early results"

Connected through hyperedge HE-3 (induced by source paper "selfish cops and passive robber qualitative games"):
  with members:
    - "simultaneously moving cops and robbers"
    - "the role of visibility in pursuit evasion games"

Connected through hyperedge HE-4 (induced by source paper "simultaneously moving cops and robbers"):
  with members:
    - "the role of visibility in pursuit evasion games"
    - "cops and robbers game theory and zermelo s early results"
    - "some remarks on cops and drunk robbers"

Connected through hyperedge HE-5 (induced by source paper "a probabilistic version of the game of zombies and survivors on graphs"):
  with members:
    - "the role of visibility in pursuit evasion games"
    - "cop and robber games when the robber can hide and ride"

Connected through hyperedge HE-6 (induced by source paper "the role of visibility in pursuit evasion games"):
  with members:
    - "heuristic search value iteration for pomdps"
    - "perseus randomized point based value iteration for pomdps"
    - "value function approximations for partially observable markov decision processes"

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.DM(Discrete Mathematics)