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: "the inverse problem for power distributions in committees"
  Abstract: Several power indices have been introduced in the literature in order to measure the influence of individual committee members on the aggregated decision. Here we ask the inverse question and aim to design voting rules for a committee such that a given desired power distribution is met as closely as possible. We present an exact algorithm for a large class of different power indices based on integer linear programming. With respect to negative approximation results we generalize the approach of Alon and Edelman who studied power distributions for the Banzhaf index, where most of the power is concentrated on few coordinates. It turned out that each Banzhaf vector of an n-member committee that is near to such a desired power distribution, has to be also near to the Banzhaf vector of a k-member committee. We show that such Alon-Edelman type results are possible for other power indices like e.g. the Public Good index or the Coleman index to prevent actions, while they are principally impossible for e.g. the Johnston index.

Connected through hyperedge HE-1 (induced by source paper "which criteria qualify power indices for applications a comment to the story of the poor public good index"):
  with members:
    - "representation compatible power indices"
    - "importance in systems with interval decisions"
    - "the power of the largest player"
    - "the cost of getting local monotonicity"
    - "mostly sunny a forecast of tomorrow s power index research"
    - "the average representation a cornucopia of power indices"
    - "measuring voting power in convex policy spaces"

Connected through hyperedge HE-2 (induced by source paper "approximating power by weights"):
  with members:
    - "representation compatible power indices"
    - "the average representation a cornucopia of power indices"
    - "the inverse shapley value problem"

Connected through hyperedge HE-3 (induced by source paper "the power of the largest player"):
  with members:
    - "the inverse shapley value problem"

Connected through hyperedge HE-4 (induced by source paper "the cost of getting local monotonicity"):
  with members:
    - "the average representation a cornucopia of power indices"

Connected through hyperedge HE-5 (induced by source paper "mostly sunny a forecast of tomorrow s power index research"):
  with members:
    - "the prediction value"
    - "group activity selection problem"
    - "the inverse shapley value problem"

Connected through hyperedge HE-6 (induced by source paper "ready for the design of voting rules"):
  with members:
    - "the inverse shapley value problem"
    - "nearly optimal solutions for the chow parameters problem and low weight approximation of halfspaces"

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)