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: "eliminating the weakest link making manipulation intractable"
  Abstract: Successive elimination of candidates is often a route to making manipulation intractable to compute. We prove that eliminating candidates does not necessarily increase the computational complexity of manipulation. However, for many voting rules used in practice, the computational complexity increases. For example, it is already known that it is NP-hard to compute how a single voter can manipulate the result of single transferable voting (the elimination version of plurality voting). We show here that it is NP-hard to compute how a single voter can manipulate the result of the elimination version of veto voting, of the closely related Coombs' rule, and of the elimination versions of a general class of scoring rules.

Connected through hyperedge HE-1 (induced by source paper "bounded incentives in manipulating the probabilistic serial rule"):
  with members:
    - "investigating the characteristics of one sided matching mechanisms under various preferences and risk attitudes"
    - "manipulating the probabilistic serial rule"
    - "social welfare in one sided matching mechanisms"
    - "an axiomatic approach to characterizing and relaxing strategyproofness of one sided matching mechanisms"
    - "decision theory with resource bounded agents"
    - "the computational complexity of random serial dictatorship"
    - "social welfare in one sided matching markets without money"
    - "truthful assignment without money"

Connected through hyperedge HE-2 (induced by source paper "x then x manipulation of same system runoff elections"):
  with members:
    - "search versus decision for election manipulation problems"
    - "an atypical survey of typical case heuristic algorithms"
    - "where are the really hard manipulation problems the phase transition in manipulating the veto rule"
    - "a richer understanding of the complexity of election systems"
    - "dichotomy for voting systems"
    - "anyone but him the complexity of precluding an alternative"
    - "universal voting protocol tweaks to make manipulation hard"

Connected through hyperedge HE-3 (induced by source paper "how hard is it to control an election by breaking ties"):
  with members:
    - "control complexity in bucklin fallback and plurality voting an experimental approach"
    - "determining possible and necessary winners under common voting rules given partial orders"
    - "manipulation of nanson s and baldwin s rules"
    - "an empirical study of the manipulability of single transferable voting"
    - "where are the really hard manipulation problems the phase transition in manipulating the veto rule"
    - "universal voting protocol tweaks to make manipulation hard"

Connected through hyperedge HE-4 (induced by source paper "how many vote operations are needed to manipulate a voting system"):
  with members:
    - "combining voting rules together"
    - "a smooth transition from powerlessness to absolute power"
    - "dominating manipulations in voting with partial information"
    - "multimode control attacks on elections"
    - "where are the really hard manipulation problems the phase transition in manipulating the veto rule"
    - "how hard is bribery in elections"
    - "universal voting protocol tweaks to make manipulation hard"

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)