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: "coalitional manipulation for schulze s rule"
  Abstract: Schulze's rule is used in the elections of a large number of organizations including Wikimedia and Debian. Part of the reason for its popularity is the large number of axiomatic properties, like monotonicity and Condorcet consistency, which it satisfies. We identify a potential shortcoming of Schulze's rule: it is computationally vulnerable to manipulation. In particular, we prove that computing an unweighted coalitional manipulation (UCM) is polynomial for any number of manipulators. This result holds for both the unique winner and the co-winner versions of UCM. This resolves an open question stated by Parkes and Xia (2012). We also prove that computing a weighted coalitional manipulation (WCM) is polynomial for a bounded number of candidates. Finally, we discuss the relation between the unique winner UCM problem and the co-winner UCM problem and argue that they have substantially different necessary and sufficient conditions for the existence of a successful manipulation.

Connected through hyperedge HE-1 (induced by source paper "a note on the complexity of manipulating weighted schulze voting"):
  with members:
    - "manipulation and control complexity of schulze voting"

Connected through hyperedge HE-2 (induced by source paper "detecting possible manipulators in elections"):
  with members:
    - "asymptotic collusion proofness of voting rules the case of large number of candidates"
    - "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"
    - "an empirical study of the manipulability of single transferable voting"

Connected through hyperedge HE-3 (induced by source paper "election attacks with few candidates"):
  with members:
    - "weighted electoral control"
    - "schulze and ranked pairs voting are fixed parameter tractable to bribe manipulate and control"
    - "a smooth transition from powerlessness to absolute power"
    - "multimode control attacks on elections"
    - "is computational complexity a barrier to manipulation"
    - "multivariate complexity analysis of swap bribery"
    - "sincere strategy preference based approval voting fully resists constructive control and broadly resists destructive control"

Connected through hyperedge HE-4 (induced by source paper "schulze and ranked pairs voting are fixed parameter tractable to bribe manipulate and control"):
  with members:
    - "weighted electoral control"
    - "search versus decision for election manipulation problems"
    - "manipulation and control complexity of schulze voting"
    - "the complexity of manipulative attacks in nearly single peaked electorates"
    - "multimode control attacks on elections"
    - "multivariate complexity analysis of swap bribery"
    - "how hard is bribery in elections"
    - "anyone but him the complexity of precluding an alternative"

Connected through hyperedge HE-5 (induced by source paper "manipulation and control complexity of schulze voting"):
  with members:
    - "search versus decision for election manipulation problems"
    - "control complexity in fallback voting"
    - "how hard is bribery in elections"
    - "hybrid elections broaden complexity theoretic resistance to control"
    - "anyone but him the complexity of precluding an alternative"

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)