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: "an empirical study of the manipulability of single transferable voting"
  Abstract: Voting is a simple mechanism to combine together the preferences of multiple agents. Agents may try to manipulate the result of voting by mis-reporting their preferences. One barrier that might exist to such manipulation is computational complexity. In particular, it has been shown that it is NP-hard to compute how to manipulate a number of different voting rules. However, NP-hardness only bounds the worst-case complexity. Recent theoretical results suggest that manipulation may often be easy in practice. In this paper, we study empirically the manipulability of single transferable voting (STV) to determine if computational complexity is really a barrier to manipulation. STV was one of the first voting rules shown to be NP-hard. It also appears one of the harder voting rules to manipulate. We sample a number of distributions of votes including uniform and real world elections. In almost every election in our experiments, it was easy to compute how a single agent could manipulate the election or to prove that manipulation by a single agent was impossible.

Connected through hyperedge HE-1 (induced by source paper "deceased organ matching in australia"):
  with members:
    - "manipulating the probabilistic serial rule"
    - "online fair division analysing a food bank problem"
    - "welfare of sequential allocation mechanisms for indivisible goods"
    - "allocation in practice"
    - "possible and necessary allocations via sequential mechanisms"
    - "fair assignment of indivisible objects under ordinal preferences"
    - "a social welfare optimal sequential allocation procedure"
    - "where are the hard manipulation problems"

Connected through hyperedge HE-2 (induced by source paper "on the likelihood of single peaked preferences"):
  with members:
    - "computational aspects of nearly single peaked electorates"
    - "the one dimensional euclidean domain finitely many obstructions are not enough"
    - "are there any nicely structured preference profiles nearby"
    - "on the computation of fully proportional representation"
    - "the complexity of manipulative attacks in nearly single peaked electorates"
    - "clone structures in voters preferences"
    - "where are the hard manipulation problems"
    - "the shield that never was societies with single peaked preferences are more open to manipulation and control"

Connected through hyperedge HE-3 (induced by source paper "complexity of manipulation with partial information in voting"):
  with members:
    - "manipulative elicitation a new attack on elections with incomplete preferences"
    - "on the exact amount of missing information that makes finding possible winners hard"
    - "complexity of manipulation in elections with partial votes"
    - "frugal bribery in voting"
    - "detecting possible manipulators in elections"
    - "kernelization complexity of possible winner and coalitional manipulation problems in voting"
    - "the computational impact of partial votes on strategic voting"
    - "possible and necessary winner problem in social polls"

Connected through hyperedge HE-4 (induced by source paper "generating single peaked votes"):
  with members:
    - "where are the hard manipulation problems"
    - "the shield that never was societies with single peaked preferences are more open to manipulation and control"
    - "where are the really hard manipulation problems the phase transition in manipulating the veto rule"
    - "eliciting single peaked preferences using comparison queries"

Connected through hyperedge HE-5 (induced by source paper "manipulation is harder with incomplete votes"):
  with members:
    - "possible and necessary winner problem in social polls"
    - "complexity of manipulation bribery and campaign management in bucklin and fallback voting"
    - "determining possible and necessary winners under common voting rules given partial orders"
    - "dominating manipulations in voting with partial information"

Connected through hyperedge HE-6 (induced by source paper "detecting possible manipulators in elections"):
  with members:
    - "asymptotic collusion proofness of voting rules the case of large number of candidates"
    - "coalitional manipulation for schulze s rule"
    - "complexity of manipulation bribery and campaign management in bucklin and fallback voting"
    - "weighted electoral control"
    - "determining possible and necessary winners under common voting rules given partial orders"
    - "manipulation of nanson s and baldwin s rules"
    - "complexity of and algorithms for borda manipulation"
    - "is computational complexity a barrier to manipulation"

Connected through hyperedge HE-7 (induced by source paper "a local dominance theory of voting equilibria"):
  with members:
    - "strategic voting and the logic of knowledge"
    - "preference elicitation for general random utility models"
    - "control complexity in bucklin fallback and plurality voting an experimental approach"
    - "a classification of weakly acyclic games"
    - "dominating manipulations in voting with partial information"
    - "equilibria of plurality voting with abstentions"

Connected through hyperedge HE-8 (induced by source paper "allocation in practice"):
  with members:
    - "a study of proxies for shapley allocations of transport costs"
    - "online cake cutting"
    - "where are the hard manipulation problems"
    - "where are the really hard manipulation problems the phase transition in manipulating the veto rule"
    - "the sat phase transition"

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)