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: "dealing with incomplete agents preferences and an uncertain agenda in group decision making via sequential majority voting"
  Abstract: We consider multi-agent systems where agents' preferences are aggregated via sequential majority voting: each decision is taken by performing a sequence of pairwise comparisons where each comparison is a weighted majority vote among the agents. Incompleteness in the agents' preferences is common in many real-life settings due to privacy issues or an ongoing elicitation process. In addition, there may be uncertainty about how the preferences are aggregated. For example, the agenda (a tree whose leaves are labelled with the decisions being compared) may not yet be known or fixed. We therefore study how to determine collectively optimal decisions (also called winners) when preferences may be incomplete, and when the agenda may be uncertain. We show that it is computationally easy to determine if a candidate decision always wins, or may win, whatever the agenda. On the other hand, it is computationally hard to know wheth er a candidate decision wins in at least one agenda for at least one completion of the agents' preferences. These results hold even if the agenda must be balanced so that each candidate decision faces the same number of majority votes. Such results are useful for reasoning about preference elicitation. They help understand the complexity of tasks such as determining if a decision can be taken collectively, as well as knowing if the winner can be manipulated by appropriately ordering the agenda.

Connected through hyperedge HE-1 (induced by source paper "is computational complexity a barrier to manipulation"):
  with members:
    - "dominating manipulations in voting with partial information"
    - "manipulation of nanson s and baldwin s rules"
    - "complexity of and algorithms for borda manipulation"
    - "an empirical study of borda manipulation"
    - "multimode control attacks on elections"
    - "an empirical study of the manipulability of single transferable voting"
    - "where are the hard manipulation problems"
    - "manipulation and gender neutrality in stable marriage procedures"

Connected through hyperedge HE-2 (induced by source paper "where are the hard manipulation problems"):
  with members:
    - "complexity of and algorithms for borda manipulation"
    - "an empirical study of the manipulability of single transferable voting"
    - "manipulation and gender neutrality in stable marriage procedures"
    - "the shield that never was societies with single peaked preferences are more open to manipulation and control"
    - "complexity of terminating preference elicitation"
    - "where are the really hard manipulation problems the phase transition in manipulating the veto rule"
    - "manipulating tournaments in cup and round robin competitions"
    - "eliciting single peaked preferences using comparison queries"

Connected through hyperedge HE-3 (induced by source paper "where are the really hard manipulation problems the phase transition in manipulating the veto rule"):
  with members:
    - "complexity of terminating preference elicitation"
    - "the sat phase transition"
    - "the g n m phase transition is not hard for the hamiltonian cycle problem"

Connected through hyperedge HE-4 (induced by source paper "manipulating tournaments in cup and round robin competitions"):
  with members:
    - "where are the really hard manipulation problems the phase transition in manipulating the veto rule"

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)