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: "the good the bad and the odd cycles in answer set programs"
  Abstract: Backdoors of answer-set programs are sets of atoms that represent clever reasoning shortcuts through the search space. Assignments to backdoor atoms reduce the given program to several programs that belong to a tractable target class. Previous research has considered target classes based on notions of acyclicity where various types of cycles (good and bad cycles) are excluded from graph representations of programs. We generalize the target classes by taking the parity of the number of negative edges on bad cycles into account and consider backdoors for such classes. We establish new hardness results and non-uniform polynomial-time tractability relative to directed or undirected cycles.

Connected through hyperedge HE-1 (induced by source paper "backdoors to normality for disjunctive logic programs"):
  with members:
    - "dual normal logic programs the forgotten class"
    - "the third open answer set programming competition"
    - "the parameterized complexity of reasoning problems beyond np"
    - "backdoors to abduction"
    - "backdoors to satisfaction"
    - "backdoors to tractable answer set programming"
    - "detecting inconsistencies in large biological networks with answer set programming"
    - "trichotomy and dichotomy results on the complexity of reasoning with disjunctive logic programs"

Connected through hyperedge HE-2 (induced by source paper "backdoors to tractable answer set programming"):
  with members:
    - "guarantees and limits of preprocessing in constraint satisfaction and reasoning"
    - "the parameterized complexity of reasoning problems beyond np"
    - "backdoors to normality for disjunctive logic programs"
    - "numvc an efficient local search algorithm for minimum vertex cover"
    - "backdoors to abduction"
    - "strong backdoors to bounded treewidth sat"
    - "strong backdoors to nested satisfiability"
    - "directed subset feedback vertex set is fixed parameter tractable"

Connected through hyperedge HE-3 (induced by source paper "backdoors to satisfaction"):
  with members:
    - "strong backdoors to bounded treewidth sat"
    - "strong backdoors to nested satisfiability"
    - "augmenting tractable fragments of abstract argumentation"
    - "backdoors to acyclic sat"
    - "3 sat faster and simpler unique sat bounds for ppsz hold in general"
    - "backdoors to tractable answer set programming"
    - "limits of preprocessing"
    - "subset feedback vertex set is fixed parameter tractable"

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)