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: "stable unstable semantics beyond np with normal logic programs"
  Abstract: Standard answer set programming (ASP) targets at solving search problems from the first level of the polynomial time hierarchy (PH). Tackling search problems beyond NP using ASP is less straightforward. The class of disjunctive logic programs offers the most prominent way of reaching the second level of the PH, but encoding respective hard problems as disjunctive programs typically requires sophisticated techniques such as saturation or meta-interpretation. The application of such techniques easily leads to encodings that are inaccessible to non-experts. Furthermore, while disjunctive ASP solvers often rely on calls to a (co-)NP oracle, it may be difficult to detect from the input program where the oracle is being accessed. In other formalisms, such as Quantified Boolean Formulas (QBFs), the interface to the underlying oracle is more transparent as it is explicitly recorded in the quantifier prefix of a formula. On the other hand, ASP has advantages over QBFs from the modeling perspective. The rich high-level languages such as ASP-Core-2 offer a wide variety of primitives that enable concise and natural encodings of search problems. In this paper, we present a novel logic programming--based modeling paradigm that combines the best features of ASP and QBFs. We develop so-called combined logic programs in which oracles are directly cast as (normal) logic programs themselves. Recursive incarnations of this construction enable logic programming on arbitrarily high levels of the PH. We develop a proof-of-concept implementation for our new paradigm. #R##N#This paper is under consideration for acceptance in TPLP.

Connected through hyperedge HE-1 (induced by source paper "the seventh answer set programming competition design and results"):
  with members:
    - "efficiently coupling the i dlv grounder with asp solvers"
    - "optimizing answer set computation via heuristic based decomposition"
    - "on the computation of paracoherent answer sets"
    - "casp solutions for planning in hybrid domains"
    - "asperix a first order forward chaining approach for answer set computing"
    - "optimizing phylogenetic supertrees using answer set programming"
    - "predicate logic as a modeling language modeling and solving some machine learning and data mining problems with idp3"
    - "dynamic consistency checking in goal directed answer set programming"

Connected through hyperedge HE-2 (induced by source paper "solving advanced argumentation problems with answer set programming"):
  with members:
    - "depqbf 6 0 a search based qbf solver beyond traditional qcdcl"
    - "the power of non ground rules in answer set programming"
    - "lpopt a rule optimization tool for answer set programming"
    - "extension based semantics of abstract dialectical frameworks"
    - "the dlv system for knowledge representation and reasoning"

Connected through hyperedge HE-3 (induced by source paper "beyond np quantifying over answer sets"):
  with members:
    - "complex optimization in answer set programming"
    - "the dlv system for knowledge representation and reasoning"
    - "towards automated integration of guess and check programs in answer set programming a meta interpreter and applications"

Connected through hyperedge HE-4 (induced by source paper "technical report inconsistency in answer set programs and extensions"):
  with members:
    - "a model building framework for answer set programming with external computations"
    - "towards automated integration of guess and check programs in answer set programming a meta interpreter and applications"
    - "a knowledge compilation map"

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)