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: "achieving fully proportional representation is easy in practice"
  Abstract: We provide experimental evaluation of a number of known and new algorithms for approximate computation of Monroe's and Chamberlin-Courant's rules. Our experiments, conducted both on real-life preference-aggregation data and on synthetic data, show that even very simple and fast algorithms can in many cases find near-perfect solutions. Our results confirm and complement very recent theoretical analysis of Skowron et al., who have shown good lower bounds on the quality of (some of) the algorithms that we study.

Connected through hyperedge HE-1 (induced by source paper "can we reach pareto optimal outcomes using bottom up approaches"):
  with members:
    - "unanimously acceptable agreements for negotiation teams in unpredictable domains"
    - "tasks for agent based negotiation teams analysis review and challenges"
    - "studying the impact of negotiation environments on negotiation teams performance"
    - "evolutionary aided negotiation model for bilateral bargaining in ambient intelligence domains with complex utility functions"
    - "reaching unanimous agreements within agent based negotiation teams with linear and monotonic utility functions"
    - "techniques for highly multiobjective optimisation some nondominated points are better than others"

Connected through hyperedge HE-2 (induced by source paper "empirical evaluation of real world tournaments"):
  with members:
    - "who can win a single elimination tournament"
    - "complexity of and algorithms for borda manipulation"

Connected through hyperedge HE-3 (induced by source paper "computational aspects of multi winner approval voting"):
  with members:
    - "properties of multiwinner voting rules"
    - "finding a collective set of items from proportional multirepresentation to group recommendation"
    - "justified representation in approval based committee voting"
    - "fully proportional representation as resource allocation approximability results"
    - "complexity of and algorithms for borda manipulation"
    - "exact analysis of dodgson elections lewis carroll s 1876 voting system is complete for parallel access to np"

Connected through hyperedge HE-4 (induced by source paper "cooperation and competition when bidding for complex projects centralized and decentralized perspectives"):
  with members:
    - "on the computation of fully proportional representation"
    - "fully proportional representation as resource allocation approximability results"
    - "false name proof mechanisms for hiring a team"
    - "frugal mechanism design via spectral techniques"

Connected through hyperedge HE-5 (induced by source paper "the complexity of fully proportional representation for single crossing electorates"):
  with members:
    - "properties of multiwinner voting rules"
    - "approximating the maxcover problem with bounded frequencies in fpt time"
    - "on the computation of fully proportional representation"
    - "fully proportional representation as resource allocation approximability results"
    - "the complexity of manipulative attacks in nearly single peaked electorates"
    - "clone structures in voters preferences"

Connected through hyperedge HE-6 (induced by source paper "approximating the maxcover problem with bounded frequencies in fpt time"):
  with members:
    - "on the computation of fully proportional representation"
    - "fully proportional representation as resource allocation approximability results"

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.MA(Multiagent Systems)