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: "complexity of super coherence problems in asp"
  Abstract: Adapting techniques from database theory in order to optimize Answer Set Programming#R##N#(ASP) systems, and in particular the grounding components of ASP systems, is an important#R##N#topic in ASP. In recent years, the Magic Set method has received some interest in this setting,#R##N#and a variant of it, called Dynamic Magic Set, has been proposed for ASP. However, this#R##N#technique has a caveat, because it is not correct (in the sense of being query-equivalent)#R##N#for all ASP programs. In a recent work, a large fragment of ASP programs, referred to as#R##N#super-coherent programs, has been identified, for which Dynamic Magic Set is correct. The#R##N# fragment contains all programs which possess at least one answer set, no matter which set of#R##N#facts is added to them. Two open question remained: How complex is it to determine whether#R##N#a given program is super-coherent? Does the restriction to super-coherent programs limit#R##N#the problems that can be solved? Especially the first question turned out to be quite difficult#R##N#   to answer precisely. In this paper, we formally prove that deciding whether a propositional#R##N#  P#R##N# P#R##N#program is super-coherent is Π3 -complete in the disjunctive case, while it is Π2 -complete for#R##N# normal programs. The hardness proofs are the difficult part in this endeavor: We proceed#R##N#  by characterizing the reductions by the models and reduct models which the ASP programs#R##N# should have, and then provide instantiations that meet the given specifications. Concerning#R##N#  the second question, we show that all relevant ASP reasoning tasks can be transformed into#R##N# tasks over super-coherent programs, although this transformation is more of theoretical than#R##N#practical interest.

Connected through hyperedge HE-1 (induced by source paper "enhancing magic sets with an application to ontological reasoning"):
  with members:
    - "shared aggregate sets in answer set programming"
    - "cautious reasoning in asp via minimal models and unsatisfiable cores"
    - "anytime answer set optimization via unsatisfiable core shrinking"
    - "rewriting recursive aggregates in answer set programming back to monotonicity"
    - "anytime computation of cautious consequences in answer set programming"
    - "vicious circle principle and logic programs with aggregates"
    - "logic programs with propositional connectives and aggregates"
    - "well founded and stable semantics of logic programs with aggregates"

Connected through hyperedge HE-2 (induced by source paper "shared aggregate sets in answer set programming"):
  with members:
    - "asp core 2 input language format"
    - "constraints lazy constraints or propagators in asp solving an empirical analysis"
    - "clingcon the next generation"
    - "combining answer set programming and domain heuristics for solving hard industrial problems application paper"
    - "anytime answer set optimization via unsatisfiable core shrinking"
    - "predicate logic as a modeling language modeling and solving some machine learning and data mining problems with idp3"
    - "complexity and compilation of gz aggregates in answer set programming"
    - "rewriting recursive aggregates in answer set programming back to monotonicity"

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.LO(Logic in Computer Science)